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E E 200 Undergraduate Research Exploration Seminar (1)
Weekly seminar featuring research primarily from within the Department of Electrical and Computer Engineering. Speakers include senior PhD students and postdocs as well as faculty from within the department. Provides students with an opportunity to connect with the broader research community in electrical and computer engineering. Credit/no-credit only.

E E 201 Computer Hardware Skills (2) RSN
Lab-based course focused on a wide range of basic hands-on skills for electrical and computer engineers. Provides an overview of topic areas and career paths in electrical and computer engineering. Topics include introduction to physical circuit building, microcontroller programming, proportional-integral-derivative design, soldering, circuit simulation, 3D design and printing, printed circuit board control, and sensors. Prerequisite: CSE 122, CSE 123, CSE 142, or CSE 143, any of which may be taken concurrently Offered: AWSp.

E E 205 Introduction to Signal Conditioning (4) RSN
Introduces analog circuits interfacing sensors to digital systems. /includes connection, attenuation, amplification, sampling, filtering, termination, controls, Kirchhoff's Laws, sources, resistors, op amps, capacitors, inductors, PSice, and MATLAB. Intended for non-EE majors. Prerequisite: either MATH 126 or MATH 136; and either PHYS 122 or PHYS 142. Offered: W.

E E 215 Fundamentals of Electrical Engineering (4) NSc
Introduction to electrical engineering. Basic circuit and systems concepts. Mathematical models of components. Kirchhoff's laws. Resistors, sources, capacitors, inductors, and operational amplifiers. Solution of first and second order linear differential equations associated with basic circuit forms. Prerequisite: either MATH 136, or MATH 126 and either MATH 207, MATH 307, or AMATH 351, any of which may be taken concurrently; and either PHYS 122 or PHYS 142.

E E 233 Circuit Theory (5)
Electric circuit theory. Analysis of circuits with sinusoidal signals. Phasors, system functions, and complex frequency. Frequency response. Computer analysis of electrical circuits. Power and energy. Two port network theory. Laboratory in basic electrical engineering topics. Course overlaps with: B EE 233. Prerequisite: E E 215.

E E 241 Programming for Signal and Information Processing Applications (2)
Introduction to programming for signal and information processing. Basic syntax and data types. Packages for data manipulation and visualization. Handling a variety of data formats. Prerequisite: either CSE 122, CSE 123, CSE 142, CSE 143, or CSE 160.

E E 242 Signals, Systems, and Data I (5)
Introduction to signal processing, including both continuous- and discrete-time signals and systems. Basic signals including impulses, unit steps, periodic signals and complex exponentials. Convolution of signals. Fourier series and transforms. Linear, time-invariant filters. Computer laboratory. Course overlaps with: E E 235; B EE 235; and B EE 341. Prerequisite: either MATH 135, MATH 207, or AMATH 351, any of which may be taken concurrently; and either E E 241, which may be taken concurrently, or CSE 163.

E E 271 Digital Circuits and Systems (5)
Overview of digital computer systems. Covers logic, Boolean algebra, combinational and sequential circuits and logic design; programmable logic devices; and the design and operation of digital computers, including ALU, memory, and I/O. Weekly laboratories. Course overlaps with: CSE 369 and B EE 271. Prerequisite: either CSE 121, CSE 122, CSE 123, CSE 142, or CSE 143.

E E 280 Exploring Devices (4)
Overview of modern electronic and photonic devices underlying modern electronic products including smartphones, traffic lights, lasers, solar cells, personal computers, and chargers. Introduction to modeling and principles of physics relevant to the analysis of electrical and optical/photonic devices. Prerequisite: E E 215, which may be taken concurrently; and either PHYS 122 or PHYS 142; recommended: either Python programming or Matlab; and Linux. Offered: AWSp.

E E 299 Introductory Topics in Electrical Engineering (1-5, max. 10) NSc
New and experimental approaches to basic electrical engineering. May include design and construction projects.

E E 321 Computing Fundamentals (4) RSN
Covers the theoretical and mathematical foundations of computation. Logic, set theory, induction, and algebraic structures with applications to computing; models of computation; limits of computability; P, NP, and NP-Complete. Course overlaps with: CSE 311. Prerequisite: either MATH 126 or MATH 136; and either CSE 123 or CSE 143.

E E 331 Devices and Circuits I (5)
Physics, characteristics, applications, analysis, and design of circuits using semiconductor diodes and field-effect transistors with an emphasis on large-signal behavior and digital logic circuits. Classroom concepts are reinforced through laboratory experiments and design exercises. Course overlaps with: B EE 331 and TCES 312. Prerequisite: 1.0 in E E 233.

E E 332 Devices and Circuits II (5)
Characteristics of bipolar transistors, large- and small- signal models for bipolar and field effect transistors, linear circuit applications, including low and high frequency analysis of differential amplifiers, current sources, gain stages and output stages, internal circuitry of op-amps, op-amp configurations, op-amp stability and compensation. Weekly laboratory. Course overlaps with: B EE 332. Prerequisite: 1.0 in E E 331.

E E 342 Signals, Systems, and Data II (4)
Review of basic signal processing concepts. Two-sided Laplace and z -transforms and connection to Fourier transforms. Modulation, sampling and the fast Fourier transform. Short-time Fourier transform. Multi-rate signal processing. Applications including inference and machine learning. Computer laboratory. Course overlaps with: E E 341 and B EE 341. Prerequisite: E E 242.

E E 351 Energy Systems (5)
Develops understanding of modern energy systems through theory and analysis of the system and its components. Discussions of generation, transmission, and utilization are complemented by environmental and energy resources topics as well as electromechanical conversion, power electronics, electric safety, renewable energy, and electricity blackouts. Course overlaps with: B EE 457. Prerequisite: a minimum grade of 1.0 in E E 215.

E E 361 Applied Electromagnetics (5)
Introductory electromagnetic field theory and Maxwell's equations in integral and differential forms; uniform plane waves in linear media; boundary conditions and reflection and transmission of waves; guided waves; transmission lines and Smith chart; electrostatics. Course overlaps with: B EE 361. Prerequisite: a minimum grade of 1.0 in E E 215; and either PHYS 123 or PHYS 143.

E E 371 Design of Digital Circuits and Systems (5)
Provides a theoretical background in, and practical experience with, tools, and techniques for modeling complex digital systems with the Verilog hardware description language, maintaining signal integrity, managing power consumption, and ensuring robust intra- and inter-system communication. Prerequisite: either E E 205 or E E 215; either E E 271 or CSE 369. Offered: jointly with CSE 371.

E E 391 Probability for Information and Communication Engineering (4)
Introduces probabilistic concepts for Electrical and Computer Engineering majors with applications to information/data science, signal processing, and communication systems. Includes accompanying Python labs that apply probabilistic concepts to these application domains. Course overlaps with: MATH 394/STAT 394. Prerequisite: E E 235 or E E 241; and MATH 126 or MATH 136.

E E 393 Advanced Technical Communication (4)
Practical skills for day-to-day engineering communication as well as an advanced exploration of how to prepare persuasive documents and presentations for technical and non-technical audiences.

E E 397 Sex and Gender in Engineering (3) DIV
Explores professional issues faced by women as well as sexual and gender minorities (LGBTQ+) in the engineering workplace.

E E 398 Introduction to Professional Issues (1)
Covers topics of interest to students planning their educational and professional path, including salaries, the value of advanced degrees, societal expectations of engineering professionals, the corporate enterprise, ethical dilemmas, patents and trade secrets, outsourcing, and the global market.

E E 399 Special Topics in Electrical Engineering (1-5, max. 10)
New and experimental approaches to current electrical engineering problems. May include design and construction projects.

E E 400 Advanced Topics in Electrical Engineering (1-5, max. 10)
Contemporary topics at the advanced undergraduate elective level. Faculty presents advanced elective topics not included in the established curriculum.

E E 406 Teaching Engineering (3) DIV
Explores effective and inclusive teaching techniques in engineering and related STEM fields. Includes active and problem-based learning with attention to how racial, ethnicity, gender, and socioeconomic differences affect how students learn and interact with teachers (including faculty and teaching assistants).

E E 414 Engineering Innovation in Health (3)
Introduces the role of Innovation and engineering in the design of medical devices and healthcare technologies, applicable both to medical practice and healthcare-focused engineering. May serve as the first course in a medically related senior design project sequence. Discusses medical practice, clinical needs finding, FDA regulation, insurance reimbursement, intellectual property, and the medical device design process. Recommended: M E 123 and M E 354. Offered: jointly with M E 414; A.

E E 416 Random Signals for Communications and Signal Processing (4)
Probability and random processes in communications. Random variables, distributions, and expectation. Statistical filter design for detection and estimation. Prerequisite: either E E 242 or E E 341; either STAT 390, MATH 394/STAT 394, or IND E 315.

E E 417 Modern Wireless Communications (4)
Introduction to wireless networks as an application of basic communication theorems. Examines modulation techniques for digital communications, signal space, optimum receiver design, error performance, error control coding for high reliability, mulitpath fading and its effects, RF link budget analysis, WiFi and Wimax systems. Course overlaps with: B EE 417. Prerequisite: E E 416

E E 418 Network Security and Cryptography (4)
Fundamental principles of cryptography and its application to network and communication security. An introduction to the fundamental tools in cryptography and the protocols that enable its application to network and communication security. Prerequisite: CSE 163 or E E 241; either MATH 136, MATH 208, or MATH 308; and either IND E 315, MATH 394/STAT 394, or STAT 390.

E E 419 Introduction to Computer-Communication Networks (4)
Computer network architectures and protocols. OSI Layers and performance analysis. Transmission media, switching, multiple access arbitration. Network routing, congestion control, flow control. Transport protocols, real-time, multicast, network security. Course overlaps with: TCES 425. Prerequisite: either CSE 122, CSE 123, CSE 142, or CSE 143; and either IND E 315, MATH 394/STAT 394, STAT 390, or STAT 391.

E E 420 Design in Communications (4)
Design projects in communications. Frequent projects solved by student teams. Reports and presentations. Prerequisite: 1.0 in E E 417 which may be taken concurrently.

E E 421 Quantum Mechanics for Engineers (3)
Covers the basic theory of quantum mechanics in the context of modern examples of technological importance involving 1D, 2D, and 3D nanomaterials. Develops a qualitative and quantitative understanding of the principles of quantization, band structure, density of states, and Fermi's golden rule (optical absorption, electron-impurity/phonon scattering). Prerequisite: either MATH 135, MATH 207, MATH 307, or AMATH 351; recommended: Calculus through differential equations.

E E 423 Introduction to Synthetic Biology (3)
Studies mathematical modeling of transcription, translation, regulation, and metabolism in cell; computer aided design methods for synthetic biology; implementation of information processing, Boolean logic and feedback control laws with genetic regulatory networks; modularity, impedance matching and isolation in biochemical circuits; and parameter estimation methods. Prerequisite: either MATH 136, MATH 207, MATH 307, AMATH 351, or CSE 311; and either MATH 208, MATH 308, or AMATH 352. Offered: jointly with BIOEN 423/CHEM E 476/CSE 486.

E E 424 Advanced Systems and Synthetic Biology (3)
Covers advanced concepts in system and synthetic biology. Includes kinetics, modeling, stoichiometry, control theory, metabolic systems, signaling, and motifs. All topics are set against problems in synthetic biology. Prerequisite: E E 423/BIOEN 423/CHEM E 476/CSE 486. Offered: jointly with BIOEN 424/CHEM E 477/CSE 487.

E E 425 Laboratory Methods in Synthetic Biology (4)
Designs and builds transgenic bacterial using promoters and genes taken from a variety of organisms. Uses construction techniques including recombination, gene synthesis, and gene extraction. Evaluates designs using sequencing, fluorescence assays, enzyme activity assays, and single cell studies using time-lapse microscopy. Prerequisite: E E 423/BIOEN 423/CHEM E 476/CSE 486; and either CHEM 142, CHEM 143, or CHEM 145. Offered: jointly with BIOEN 425/CHEM E 478/CSE 488.

E E 433 Analog Circuit Design (5)
Design of analog circuits and systems applying modern integrated circuit technology: operational amplifiers, differential amplifiers, active filters, voltage references and regulators. Prerequisite: 1.0 in E E 332.

E E 436 Medical Instrumentation (4)
Introductory course in the application of instrumentation to medicine. Topics include transducers, signal-conditioning amplifiers, electrodes and electrochemistry, ultrasound systems, electrical safety, and the design of clinical electronics. Laboratory included. For upper-division and first-year graduate students preparing for careers in bioengineering - both research and industrial. Prerequisite: E E 332.

E E 437 Integrated Systems Capstone (5)
Team-based design experience to develop integrated electronic systems by constructing and validating, prototype integrated circuits (IC) and sensors using modern Computer Aided Design (CAD) tools. Systems are simulated using modern semiconductor, MEMs and nanophotonic technologies. Teams define requirements; investigate tradeoffs in performance, cost, power and size; design for both reliability and testability. Prerequisite: E E 331 and E E 473.

E E 438 Instrumentation Design Project Capstone (5)
Team-based design for developing an electronic instrumentation system and constructing and validating a prototype using modern printed circuit board technology. Teams develop design requirements; investigate tradeoffs for miniaturization, integration, performance, and cost; and consider use cases, failure modes, manufacturability, and testability. Includes extensive laboratory. Prerequisite: either E E 433 or E E 436.

E E 440 Introduction to Digital Imaging Systems (4)
Image representation and standards, visual perception and color spaces, spatial domain image filtering and enhancement, image restoration, image transforms, image and video coding, image geometrical transformation and camera modeling. Prerequisite: E E 341 or E E 342.

E E 442 Digital Signals and Filtering (3)
Methods and techniques for digital signal processing. Review of sampling theorems, A/D and D/A converters. Demodulation by quadrature sampling. Z-transform methods, system functions, linear shift-invariant systems, difference equations. Signal flow graphs for digital networks, canonical forms. Design of digital filters, practical considerations, IIR and FIR filters. Digital Fourier transforms and FFT techniques. Prerequisite: a minimum grade of 1.0 in either E E 341 or E E 342.

E E 443 Machine Learning for Signal Processing Applications (4)
Application of machine learning and deep learning algorithms to real-world signal, image, and video processing problems using cloud computing with central, graphics, and tensor processing units (CPU/GPU/TPU). Characteristics of multi-dimensional signals and systems. Unsupervised and supervised learning. Deep learning convolutional neural networks. Generative adversarial learning. Open long-tailed recognition. Object detection and segmentation. Course overlaps with: TEE 461. Prerequisite: a minimum grade of 1.0 in E E 242; MATH 136 or MATH 208; and either IND E 315, MATH 394/STAT 394, or STAT 390.

E E 445 Fundamentals of Optimization and Machine Learning (4)
Introduction to optimization and machine learning models motivated by their application in areas including statistics, decision-making and control, and communication and signal processing. Topics include convex sets and functions, convex optimization problems and properties, convex modeling, duality, linear and quadratic programming, with emphasis on usage in machine learning problems including regularized linear regression and classification. Prerequisite: either MATH 224 or MATH 324; either MATH 136, MATH 208, MATH 308, or AMATH 352; and either E E 235, E E 242, or CSE 163.

E E 447 Control System Analysis I (4)
Linear Servomechanism theory and design principles. Pole-zero analysis, stability of feedback systems by root locus and real-frequency response methods. Design methods of Bode and Nichols. Introduction to advanced topics in automatic control theory, state variable methods. Course overlaps with: B EE 447. Prerequisite: E E 233; either E E 235 or E E 242; and either MATH 136, MATH 208, or MATH 308.

E E 448 Systems, Controls, and Robotics Capstone (4-)
In-depth control engineering design experience in small design teams. Includes project planning and management, reporting, and technical communication. Student teams design, implement, test, and report on their project results, Includes lectures on selected topics, e.g., project management, intellectual property, and some control engineering topics. Prerequisite: E E 447.

E E 449 Systems, Controls, and Robotics Capstone (-4)
In-depth control engineering design experience in small design teams. Includes project planning and management, reporting, and technical communication. Student teams design, implement, test, and report on their project results, Includes lectures on selected topics, e.g., project management, intellectual property, and some control engineering topics. Prerequisite: E E 448.

E E 451 Wind Energy (4)
Covers the operation and modeling of wind energy, wind statistics, wind generators and converters, wind energy systems, challenges to wind energy development, impacts of wind energy on the power grid, and existing and potential solutions to wind energy integration. Prerequisite: E E 351. Offered: odd years.

E E 452 Power Electronics Design (5)
Electronic conversion and control of electrical power. Includes semiconductor switching devices, power converter circuits, design of magnetics, and control of power converters. Also ac/ac, ac/dc, and dc/dc power converters; circuit simulation; extensive laboratory work; a four-week power converter design project. Course equivalent to: TEE 417. Prerequisite: a minimum grade of 1.0 in E E 233.

E E 453 Electric Drives (5)
Elements of drive systems, speed-torque characteristics of electric motors and industrial loads, solid-state converter. Starting and braking methods of loaded motors. Speed control of electric motors. Solid-state drives. Transient analysis of loaded motors. Special forms of individual- and multimotor drives. Prerequisite: a minimum grade of 1.0 in E E 452; and a minimum grade of 1.0 in E E 458.

E E 454 Power System Analysis (4)
Introduction to methods of analyzing power systems. Includes symmetrical components, calculation of line parameters, representation of transmission lines and power components, and power flow control. Course overlaps with: B EE 478. Prerequisite: 1.0 in E E 351.

E E 455 Power System Dynamics and Protection (4)
Analysis of symmetrical and unsymmetrical power systems' networks, fault analysis, and stability studies. Course overlaps with: B EE 478. Prerequisite: 1.0 in E E 351.

E E 456 Computer-Aided Design in Power Systems (4)
Design-oriented course in power system engineering. Students are assigned a project concerning system operation and planning, steady-state and dynamic behaviors of power systems, or distribution systems. Each involves formulation of design criteria, development of approach, application of existing software. Prerequisite: either 1.0 in E E 454 or 1.0 in E E 455.

E E 457 Electric Energy Distribution Systems (4)
Introduction to electric utility distribution systems. Primary and secondary network analysis and design, distribution substation problems, distribution transformers, capacitor application, overcurrent and overvoltage protection. System planning and reliability. Prerequisite: 1.0 in E E 351.

E E 458 Power Electronics Controls (5)
Theory, design, and analysis of closed-loop controllers for power electronics circuits. Emphasis will be placed on modern control methods using digital control. Prerequisite: E E 447 and E E 452; recommended: circuits; control systems; and power electronics.

E E 460 Neural Engineering (3)
Introduces the field of Neural Engineering: overview of neurobiology, recording and stimulating the nervous system, signal processing, machine learning, powering and communicating with neural devices, invasive and non-invasive brain-machine interfaces, spinal interfaces, smart prostheses, deep-brain stimulators, cochlear implants and neuroethics. Heavy emphasis on primary literature. Prerequisite: either BIOL 130, BIOL 162, or BIOL 220; and either MATH 208, AMATH 301, or AMATH 352. Offered: jointly with BIOEN 460; A.

E E 461 Neural Engineering Tech Studio (4)
Neural engineering design and translational engineering. Groups design, build and present a neural engineering prototype project to a panel of industry judges. Prerequisite: BIOEN 460/E E 460. Offered: jointly with BIOEN 461.

E E 462 Electromagnetics I: Microwave Engineering (4)
Covers microwave transmission line models and their applications; electromagnetic waves in layered media; mode structures in metallic and dielectric waveguides; resonators and cavities; and Green's functions. Prerequisite: minimum grade of 1.0 in E E 361.

E E 463 Microwave Electronic Design (4)
Design of microwave circuits using S-parameter techniques. Measurement techniques, CAD of microwave systems. Includes design, fabrication, and evaluation of a microwave amplifier. Prerequisite: E E 361; E E 332, which may be taken concurrently.

E E 464 Antennas: Analysis and Design (4)
Fundamentals of antennas, analysis, synthesis, and computer-aided design, and applications in communications, remote sensing, and radars. Radiation pattern, directivity, impedance, wire antennas, arrays, numerical methods for analysis, horn antennas, microstrip antennas, and reflector antennas. Prerequisite: 1.0 in E E 361.

E E 465 Network and Web Security (4)
Fundamental principles of network and communication security, associated vulnerabilities and defenses, and network and web security attacks. Design of security mechanisms and protocols for thwarting attacks on existing and emerging computer networks including network communication protocols, domain name systems, wireless networks, and web security. Practical protocols and analysis of their weaknesses and approaches to strengthen them. Prerequisite: either CSE 163 or E E 241; and E E 418; recommended: E E 419.

E E 466 Neural Computation and Engineering Laboratory (4) NSc
Introduces neural recording and quantitative analysis techniques to students with a background in quantitative methods. Prerequisite: either BIOL 130, BIOL 162, BIOL 220, AMATH 342; and either MATH 208, AMATH 301, or AMATH 352. ; recommended: courses in scientific computing and matrix manipulations in Matlab; and courses in neural signal processing and data analysis. Offered: jointly with BIOEN 466.

E E 467 Machine Learning for Cybersecurity (4)
Application of machine learning algorithms to cybersecurity. Anomaly detection, spam detection and IP blacklisting, use of natural language processing to improve performance in architecture identification. Optimization methods for determining adversarial inputs to bias the detection and classification outputs of deep neural networks (DNN). Backdoor trigger embedding in DNN. Generative Adversarial Networks. Hands-on, practical course. Prerequisite: either CSE 163 or E E 241; either AMATH 352, MATH 208, MATH 308, or MATH 136; and either IND E 315 , MATH 394/STAT 394, or STAT 390; recommended: E E 445.

E E 468 Software and Embedded Systems Security (4) RSN
Fundamental principles of software and embedded system security and their application to network, web, and embedded systems. Introduction to the practical tools used for software security, cryptography, and protocols that enable its application to network and system security. Course overlaps with: CSE 484. Prerequisite: E E 241 or CSE 163; recommended: E E 469/CSE 469 or E E 472.

E E 469 Computer Architecture I (5)
Introduction to computer architecture. Assembly and machine language, microprocessor organization including control and datapath. Computer arithmetic. Memory systems and caching. Performance modeling of microprocessors. Prerequisite: either E E 271 or CSE 369; and either CSE 123 or CSE 143. Offered: jointly with CSE 469.

E E 470 Computer Architecture II (4)
Advanced computer architecture. Performance evaluation and energy efficiency. Instruction set architectures. Instruction-level parallelism. Modern microprocessor micro-architecture. Thread-level parallelism. Cache coherency and memory consistency in shared-memory multiprocessors. Memory hierarchy. GPU architecture. Warehouse-scale computing. Trends in computer design. Prerequisite: either CSE 469 or E E 469. Offered: jointly with CSE 470.

E E 472 Real-Time and Embedded Operating Systems (4) RSN
Software-intensive course in modern operating systems, with a focus on real-time (RT) and embedded applications. Covers a range of topics from the classical OS concepts to RT operating systems, including the OS kernel--process and task abstraction, scheduling, concurrency, memory management, file systems and IOs, RTOS, and case studies of RTOS programming for Bluetooth or IoT networking. Prerequisite: CSE 373 and CSE 374.

E E 473 Linear Integrated Circuits (5)
Design of linear integrated circuits applying modern MOS and BJT integrated circuit technologies: single-stage amplifiers; current-mirror DC bias and active load circuits; stability and frequency compensation of single-stage and two-stage operational amplifiers; output stages; current and voltage reference circuits. Prerequisite: 1.0 in E E 332.

E E 474 Introduction to Embedded Systems (4)
Introduces the specification, design, development, and test of real time embedded system software. Use of a modern embedded microcomputer or microcontroller as a target environment for a series of laboratory projects and a comprehensive final project. Course overlaps with: CSE 451; B ME 460; CSS 427; and TCES 460. Prerequisite: CSE 123 or CSE 143 Offered: jointly with CSE 474; AWSpS.

E E 475 Embedded Systems Capstone (5)
Capstone design experience. Prototype a substantial project mixing hardware, software, and communications. Focuses on embedded processors, programmable logic devices, and emerging platforms for the development of digital systems. Provides a comprehensive experience in specification, design, and management of contemporary embedded systems. Course overlaps with: TME 441. Prerequisite: E E 271 or CSE 369; and E E 472 or CSE 474/E E 474. Offered: jointly with CSE 475.

E E 476 Introduction to Very Large-Scale Integrated Design (5)
Breadth-first introduction to digital VLSI design. Integrated CMOS logic design. CMOS logic delay and power analysis. Introduction to IC- mask-layout, gate-sizing, VLSI building blocks (adders, multipliers, counters, shifters etc.), design for testability, and memory. Projects involve some layout design, and mostly transistor and gate-level schematic design. Prerequisite: E E 215; and either E E 271 or CSE 369; recommended: basic circuit theory and basic digital design experience.

E E 477 VLSI II (5)
Provides a fairly deep understanding of how IC-based memory and datapath blocks are designed using static and dynamic CMOS technologies. Gives students extensive experience with industry-standard computer-aided design tools, including Cadence (Virtuoso, DRC, LVS) and Avanti (Hspice). Prerequisite: E E 469/CSE 469.

E E 478 Capstone Integrated Digital Design Projects (5)
VLSI-capstone course. A more detailed examination of building high-performance or low-energy integrated circuits. Wire design, timing-elements, clock generation, distribution and control, dynamic-logic, low-power design. Cannot be taken if credit received for E E 526. Prerequisite: E E 331; E E 332, which may be taken concurrently; E E 476; and E E 477; recommended: introduction to VLSI design and knowledge of ASIC design flows.

E E 479 High-Performance Graphics Processing Unit Computing (4) RSN
Introduction to high performance computing (HPC) and graphics processing units (GPUs). GPU based systems, microarchitectures, memory hierarchies, programming models, and general strategies to harness their computational power. Prerequisite: CSE 373 and CSE 374.

E E 482 Semiconductor Devices (4)
Fundamentals of state-of-the-art semiconductor devices and emerging semiconductor technologies including diodes, LEDs, solar cells, photodetectors, MOS field-effect transistors, power transistors, and nanoscale devices. In-depth analysis of devices using carrier diffusion, drift, effective mass, and density of states. Prerequisite: E E 331.

E E 484 Sensors and Sensor Systems (4)
Introduction to optical and solid-state chemical and physical sensors. Topics include transduction mechanisms, design parameters, fabrication methods and applications. Prerequisite: E E 331.

E E 486 Fundamentals of Integrated Circuit Technology (3)
Processing physics, chemistry, and technology, including evaporation, sputtering, epitaxial growth, diffusion, ion implantation, laser annealing, oxidation, chemical vapor deposition, photoresists. Design considerations for bipolar and MOS devices, materials and process characterization. Future trends. Prerequisite: EE 331 or MSE 351. Offered: jointly with MSE 486; AW.

E E 487 Introduction to Photonics (4)
Introduction to optical principles and phenomena. Topics include electromagnetic theory of light, optical interference, diffraction, polarization, optical waveguides, and optical fibers. Course overlaps with: E E 485. Prerequisite: either E E 361, PHYS 123, or PHYS 143.

E E 488 Advanced Photonics (4)
In-depth understanding and learning of advanced subjects in photonics. Topics include optical resonance, quantum nature of light and optical transitions, optical amplification, laser operation, and photodetection. Prerequisite: E E 485 or E E 487.

E E 490 Reading and Research (1-5, max. 25)
Reading and research in the field under supervision of an E E faculty member. Credit/no-credit only.

E E 491 Undergraduate Seminar (1, max. 2)
Weekly seminars on current topics in electrical engineering. Credit/no-credit only.

E E 492 Electrical Engineering Leadership Seminar (1)
Weekly seminar with program alumni presenting their workforce experience, demonstrating the depth and breadth possible in the field and best practices. Credit/no-credit only.

E E 496 Engineering Entrepreneurial Systems and Design (2)
Fundamentals of systems engineering methods, system life cycle, project management and scheduling, trade studies, risk mitigation, configuration management, budgeting, procurement, prototyping, technical reviews, and associated tools; startup life cycle, intellectual property, trade secrets, patents, startup financing, incorporation, business plan, market research, roles of officers.

E E 497 Engineering Entrepreneurial Capstone (4-)
Completion of an industry-motivated and mentored engineering project to develop design skills. Overseen by UW Faculty and guided by practicing engineers sponsored by industry. Emphasizes cross-disciplinary teamwork.

E E 498 Engineering Entrepreneurial Capstone (-4)
Completion of an industry-motivated and mentored engineering project to develop design skills. Overseen by UW Faculty and guided by practicing engineers sponsored by industry. Emphasizes cross-disciplinary teamwork. Prerequisite: E E 497.

E E 499 Undergraduate Research and Special Projects (1-5, max. 10)
Undergraduate research or design project carried out under the supervision of a faculty sponsor.

E E 500 Graduate Seminar (1, max. 9)
Weekly seminars on current topics in electrical engineering. More than one section may be offered in a given quarter. Credit/no-credit only.

E E 501 Academic Writing (4)
Develops formal technical writing skills for graduate engineering students. Covers organization and structure of archival papers, theses, reports, and proposals; concise technical language; terminology; literature search; peer review process; analysis of grammatical and stylistic errors; organization of multi-authored writing and implementation of figures, equations, and citations.

E E 503 Modeling of MEMS (4)
Microelectro mechanical systems (MEMS) including lumped modeling, conjugate power variables, electrostatic and magnetic actuators, linear transducers, linear system dynamics, design optimization, and thermal analysis. Numerical modeling topics include electro (quasi) static, mechanical, electro mechanical, magneto (quasi) static, and fluidic phenomena; parametric analysis, visualization of multi-dimensional solutions; and verification of results. Offered: jointly with MSE 505.

E E 504 Introduction to Microelectro Mechanical Systems (4)
Theoretical and practical aspects in design, analysis, and fabrication of MEMS devices. Fabrication processes, including bulk and surface micromachining. MEMS design and layout. MEMS CAD tools. Mechanical and electrical design. Applications such as micro sensors and actuators, or chemical and thermal transducers, recent advances. Course overlaps with: EE P 504. Offered: jointly with M E 504/MSE 504.

E E 505 Probability and Random Processes (4)
Foundations for the engineering analysis of random processes: set theoretic fundamentals, basic axioms of probability models, conditional probabilities and independence, discrete and continuous random variables, multiple random variables, sequences of random variables, limit theorems, models of stochastic processes, noise, stationarity and ergodicity, Gaussian processes, power spectral densities. Prerequisite: graduate standing and understanding of probability at the level of E E 416.

E E 506 Fundamentals of Wireless Communication (4)
Fundamentals of wireless communications: signals, modulation, coding, channel estimation, fading channels; performance metrics. Course overlaps with: B EE 517 and TECE 569. Prerequisite: E E 505.

E E 508 Stochastic Processes in Engineering (3)
Non-measure theoretic introduction to stochastic processes. Topics include Poisson processes, renewal processes, Markov and semi-Markov processes, Brownian motion, and martingales, with applications to problems in queuing, supply chain management, signal processing, control, and communications. Prerequisite: E E 505. Offered: jointly with IND E 508.

E E 510 Mathematical Foundations of Systems Theory (4)
Mathematical foundations for system theory presented from an engineering viewpoint. Includes set theory; functions, inverse functions; metric spaces; finite dimensional linear spaces; linear operators on finite dimensional spaces; projections on Hilbert spaces. Applications to engineering systems stressed. Offered: jointly with A A 510/CHEM E 510/M E 510.

E E 511 Introduction to Statistical Learning (4)
Covers classification and estimation of vector observations, including both parametric and nonparametric approaches. Includes classification with likelihood functions and general discriminant functions, density estimation, supervised and unsupervised learning, feature reduction, model selection, and performance estimation. Prerequisite: either E E 505 or CSE 515.

E E 512 Graphical Models in Pattern Recognition (4)
Bayesian networks, Markov random fields, factor graphs, Markov properties, standard models as graphical models, graph theory (e.g., moralization and triangulation), probabilistic inference (including pearl's belief propagation, Hugin, and Shafer-Shenoy), junction threes, dynamic Bayesian networks (including hidden Markov models), learning new models, models in practice. Prerequisite: E E 508; E E 511.

E E 514 Information Theory I (4)
Includes entropy, mutual information, Shannon's source coding theorem, data compression to entropy limit, method of types, Huffman coding, Kraft inequality, arithmetic coding, Kolmogorov complexity, communication at channel capacity (channel coding), coding theory, introduction to modern statistical coding techniques, differential entropy, and Gaussian channels. Prerequisite: E E 505.

E E 515 Information Theory II (4)
Includes advanced modern statistical coding techniques (statistical coding), advanced codes and graphs, source coding with errors (rate distortion), alternating minimization principles, channel coding with errors, network information theory, multiple description coding, and information theory in other areas including pattern recognition, bio-informatics, natural language processing, and computer science. Prerequisite: E E 514.

E E 516 Computer Speech Processing (4)
Introduction to automatic speech processing. Overview of human speech production and perception. Fundamental theory in speech coding, synthesis and reproduction, as well as system design methodologies. Advanced topics include speaker and language identification and adaptation. Prerequisite: E E 505; E E 518.

E E 517 Continuous-Space Language Processing (4)
Introduction to human language technology, with in-depth coverage of continuous-space statistical models of language and application to natural language processing tasks. Methods covered include low rank distributional representations, neural networks, and log bilinear statistical models, which are leveraged for language modeling, similarity scoring, classification, and translation/generation. Prerequisite: E E 505.

E E 518 Digital Signal Processing (4)
Covers discrete-time processing of continuous-time signals; sampling rate conversion; frequency magnitude, phase delay, and group delay; design techniques for non-recursive (FIR) filters; multirate signal processing; all-pass/minimum phase decompositions; discrete Fourier transforms, fast Fourier transforms; overlap-add; short-time Fourier analysis; and filter banks. Includes applications such as machine learning. Course overlaps with: EE P 518; B EE 511; and TECE 563. Prerequisite: E E 442; recommended: Cannot be taken for credit if credit received for EE P 518.

E E 519 Stochastic Analysis of Data From Physical Systems (4)
Computer systems for acquisition and processing of stochastic signals. Calculation of typical descriptors of such random processes as correlation functions, spectral densities, probability densities. Interpretation of statistical measurements made on a variety of physical systems (e.g., electrical, mechanical, acoustic, nuclear). Lecture plus laboratory. Prerequisite: E E 505.

E E 520 Spectral Analysis of Time Series (4)
Estimation of spectral densities for single and multiple time series. Nonparametric estimation of spectral density, cross-spectral density, and coherency for stationary time series, real and complex spectrum techniques. Bispectrum. Digital filtering techniques. Aliasing, prewhitening. Choice of lag windows and data windows. Use of the fast Fourier transform. Prerequisite: either STAT 342, STAT 390, STAT 509/CS&SS 509/ECON 580, or IND E 315. Offered: jointly with STAT 520.

E E 521 Quantum Mechanics for Engineers (4)
Covers the basic theory of quantum mechanics in the context of modern examples of technological importance involving 1D, 2D, and 3D nanomaterials. Develops a qualitative and quantitative understanding of the principles of quantization, band structure, density of states, and Fermi's golden rule (optical absorption, electron-impurity/phonon scattering). Prerequisite: MATH 207 or AMATH 351.

E E 522 Quantum Information Practicum (4)
Team-based experience solving quantum engineering problems. Student teams design, implement, and test solutions to real-world problems. Includes project planning, project management, and technical communication components. Prerequisite: either PHYS 521, CHEM 561/MSE 561, or permission of instructor; recommended: practical experience with cloud-based quantum processors. Offered: Sp.

E E 523 Introduction to Synthetic Biology (3)
Studies mathematical modeling of transcription, translation, regulation, and metabolism in cell; computer aided design methods for synthetic biology; implementation of information processing, Boolean logic and feedback control laws with genetic regulatory networks; modularity, impedance matching and isolation in biochemical circuits; and parameter estimation methods. Prerequisite: either MATH 136, MATH 207, MATH 307, AMATH 351, or CSE 311; and either MATH 208, MATH 308, or AMATH 352. Offered: jointly with BIOEN 523/CHEM E 576/CSE 586/MOLENG 525.

E E 524 Advanced Systems and Synthetic Biology (3)
Covers advanced concepts in system and synthetic biology. Includes kinetics, modeling, stoichiometry, control theory, metabolic systems, signaling, and motifs. All topics are set against problems in synthetic biology. Prerequisite: E E 523/BIOEN 523/CHEM E 576/CSE 586/MOLENG 525. Offered: jointly with BIOEN 524/CHEM E 577/CSE 587.

E E 525 VLSI II (5)
Analyzes how IC-based memory and datapath blocks are designed using static and dynamic CMOS technologies. Gives students extensive experience with industry-standard computer-aided design tools, including Cadence (Virtuoso, DRC, LVS) and Avanti (Hspice). Course overlaps with: TECE 521. Prerequisite: either E E 371/CSE 371, or E E 469/CSE 469.

E E 526 Capstone Integrated Digital Design Projects (5)
Very large-scale integration (VLSI) capstone course. A more detailed examination of building high-performance or low-energy integrated circuits. Wire design, timing-elements, clock generation, distribution and control, dynamic-logic, low-power design. Cannot be taken if credit received for E E 478. Course overlaps with: TECE 521. Prerequisite: E E 331; E E 332, which may be taken concurrently; E E 476; and either E E 477 or E E 525; recommended: introduction to VLSI design and knowledge of application-specific integrated circuit (ASIC) design flows.

E E 527 Microfabrication (4)
Principles and techniques for the fabrication of microelectronics devices and integrated circuits. Includes clean room laboratory practices and chemical safety, photolithography, wet and dry etching, oxidation and diffusion, metallization and dielectric deposition, compressed gas systems, vacuum systems, thermal processing systems, plasma systems, and metrology. Extensive laboratory with limited enrollment. Course overlaps with: EE P 527. Recommended: Cannot be taken for credit if credit received for EE P 527.

E E 528 Quantum Optics for Quantum Information Applications (4)
Topics include mathematical methods for quantum optics, quantization of the electromagnetic field, quantum states of optical systems, open quantum systems, quantum distribution theory, quantum correlation functions, atom classical field interactions, atom-quantum field (photon) interactions, collective effects in multi-atom systems. Prerequisite: MATH 207; MATH 208; and E E 521.

E E 529 Semiconductor Optoelectronics (4)
Covers optical processes in semiconductors; optical waveguide theory; junction theory; LEDs; lasers photodetectors; photovoltaics; and optical modulators and switches. Prerequisite: E E 485. Offered: jointly with MSE 529.

E E 530 Wavelets: Data Analysis, Algorithms, and Theory (3)
Review of spectral analysis. Theory of continuous and discrete wavelets. Multiresolution analysis. Computation of discrete wavelet transform. Time-scale analysis. Wavelet packets. Statistical properties of wavelet signal extraction and smoothers. Estimation of wavelet variance. Prerequisite: college-level coursework in Fourier theory and linear algebra; and either STAT 390/MATH 390, STAT 509/CS&SS 509/ECON 580, STAT 513, or IND E 315. Offered: jointly with STAT 530; Sp.

E E 531 Semiconductor Devices and Device Simulation (4)
Physical principles in semiconductor devices. Generation, recombination, p-n junctions, MOS, metal-semiconductor and other interface structures. Carrier transport at low and high level injection levels. Device simulation used to demonstrate physical principles and basic device operation. Project using device simulation. Prerequisite: E E 482.

E E 532 Power Electronics Design (5)
Electronic conversion and control of electrical power. Includes semiconductor switching devices, power converter circuits, design of magnetics, and control of power converters. Also ac/ac, ac/dc, and dc/dc power converters; circuit simulation; extensive laboratory work; a four-week power converter design project. Offered: A.

E E 533 Power Electronics Contols (5)
Theory, design, and analysis of closed-loop controllers for power electronics circuits. Emphasis on modern control methods using digital control. Prerequisite: either E E 452 or E E 532. Offered: W.

E E 534 Electric Drives (5)
Analysis and design of dc-dc converters and dc-ac drives with closed-loop digital control; printed circuit board layout, component selection, circuit debugging, and programming of embedded control systems. Includes use of circuit simulators and application of circuit analysis methods. Course overlaps with: TECE 539. Prerequisite: a minimum grade of 1.0 in either E E 458 or E E 533.

E E 535 Applied Nanophotonics (4)
Concepts of optics at wave-length, scale-structured medium. Topics include photonic crystal, dielectric and metallic optical resonators, and meta-photonic devices. Introduction to cavity quantum electrodynamics. Students learn about nanoscale photonic devices, via literature survey, problem solving and numerical simulations. Prerequisite: either E E 361, PHYS 321, or equivalent course or experience with nanophotonics.

E E 536 Design of Analog Integrated Circuits and Systems (4)
Design of analog VLSI: specifications, design, simulation, layout. Covering CMOS and Bi CMOS technologies. Course overlaps with: TECE 521 and TECE 523. Prerequisite: E E 433.

E E 537 Computation Methods for Circuit Analysis and Simulation (3)
Introduction to numerical algorithms and computer-aided techniques for the simulation of electronic circuits. Theoretical and practical aspects of important analyses: large-signal nonlinear DC, small-signal AC, nonlinear transient, and large-signal steady-state. Simulation concepts applied to the modeling and characterization of various electronic devices.

E E 538 Topics in Electronic Circuit Design (1-5, max. 16)
Topics of current interest in electronic circuit and system design. Course content varies from year to year, based on current professional interests of the faculty member in charge.

E E 539 Advanced Topics in Solid-State Electronics (1-5, max. 16)
Lectures or discussions of topics of current interest in the field of solid-state electronics for advanced graduate students having adequate preparation in solid-state theory. Subject matter may vary according to the interests of students and faculty.

E E 541 Automatic Layout of Integrated Circuits (4)
Examines the algorithms behind the following commonly used physical design automation tools: floorplanning, partitioning, placement, routing, compaction, and verification. Prerequisite: either E E 271or CSE 370; CSE 143.

E E 542 Advanced Embedded Systems Design (5)
Studies advanced embedded system design principles and practices. Emphasizes formal design methodologies such as hardware-software co-design, investigates techniques for performance optimization, and examines distributed embedded systems. Course overlaps with: TECE 512. Prerequisite: E E 478.

E E 543 Models of Robot Manipulation (4)
Mathematical models of arbitrary articulated robotic (or biological) arms and their application to realistic arms and tasks, including the homogeneous coordinate model of positioning tasks, the forward and inverse kinematic models, the Jacobian Matrix, and the recursive Newton-Euler dynamic model. Prerequisite: linear algebra.

E E 544 Computer Systems Architecture (4)
Notations for computer systems. Processor design (single chip, look-ahead, pipelined, data flow). Memory hierarchy organization and management (virtual memory and caches). Microprogramming. I/O processing. Multiprocessors (SIMD and MIMD). Course overlaps with: TECE 510. Prerequisite: CSE 451. Offered: jointly with CSE 548.

E E 545 High-Performance Computer Architectures (4)
Algorithm design, software techniques, computer organizations for high-performance computing systems. Selected topics from: VLSI complexity for parallel algorithms, compiling techniques for parallel and vector machines, large MIMD machines, interconnection networks, reconfigurable systems, memory hierarchies in multiprocessors, algorithmically specialized processors, data flow architectures. Course overlaps with: TECE 510. Prerequisite: CSE 548/E E 544. Offered: jointly with CSE 549.

E E 546 Advanced Topics in Control System Theory (1-5, max. 16)
Topics of current interest in control system theory for advanced graduate students with adequate preparation in linear and nonlinear system theory. Prerequisite: permission of instructor. Offered when adequate enrollment develops prior to close of advance registration.

E E 547 Linear Systems Theory (4)
Linearity, linearization, finite dimensionality, time-varying vs. time-invariant linear systems, interconnection of linear systems, functional/structural descriptions of linear systems, system zeros and invertibility, linear system stability, system norms, state transition, matrix exponentials, controllability and observability, realization theory. Course overlaps with: EE P 547; M E 547; TECE 551; and TECE 555. Prerequisite: E E 510/A A 510/CHEM E 510/M E 510. Offered: jointly with A A 547.

E E 548 Linear Multivariable Control (3)
Introduction to MIMO systems, successive single loop design comparison, Lyapunov stability theorem, full state feedback controller design, observer design, LQR problem statement, design, stability analysis, and tracking design. LQG design, separation principle, stability robustness. Course overlaps with: A E 513. Prerequisite: A A 547/E E 547/M E 547. Offered: jointly with A A 548/M E 548.

E E 549 Estimation and System Identification (3)
Fundamentals of state estimation for linear and nonlinear systems. Discrete and continuous systems. Probability and stochastic systems theory. Models with noise. Kalman-Bucy filters, extended Kalman filters, recursive estimation. Numerical issues in filter design and implementation. Course overlaps with: A E 514 and TECE 555. Prerequisite: either A A 547, E E 547, or M E 547. Offered: jointly with A A 549/M E 549.

E E 550 Nonlinear Optimal Control (3)
Calculus of variations for dynamical systems, definition of the dynamic optimization problem, constraints and Lagrange multipliers, the Pontryagin Maximum Principle, necessary conditions for optimality, the Hamilton-Jacobi-Bellman equation, singular arc problems, computational techniques for solution of the necessary conditions. Offered: jointly with A A 550/M E 550.

E E 551 Wind Energy (4)
Covers the operation and modeling of wind energy, wind statistics, wind generators and converters, wind energy systems, challenges to wind energy development, impacts of wind energy on the power grid, and existing and potential solutions to wind energy integration. Prerequisite: E E 351.

E E 552 Power Systems Dynamics and Control (4)
Advanced computer modeling and analysis of power systems. Application of modern systems and control theories. Course overlaps with: TECE 531. Prerequisite: E E 351 and E E 455.

E E 553 Power System Economics (4)
Economic structure of power systems. Problem formulation, optimization methods and programming for economic analysis of power system operation and planning. Economic dispatch, load forecasting, unit commitment, interchange, planning and reliability analysis. Provides background to pursue advanced work in planning and operation. Course overlaps with: EE P 553.

E E 554 Large Electric Energy Systems Analysis (4)
Deals with problems whose solution depends upon the inversion of sparse matrices that occur in the planning and operational studies of large interconnected energy systems. Application studies include system model development, state estimation, and load flow. Prerequisite: E E 456.

E E 557 Dynamics of Controlled Systems (4)
Explores control techniques for high precision motion control. Covers sate variable feedback of linear and nonlinear, multivariable systems in depth. Uses physical system modeling, graphical analysis, and numerical analysis to describe system performance. Uses simulation mini-projects to emphasize the dynamics of controlled systems and their performance.

E E 558 Substation and Distribution Automation (4)
Examines how smart grid technologies affect substation and distribution operations and how history, customer expectations, and state and federal policies have shaped the existing infrastructure. Studies the capabilities of various emerging technologies to assess how they are able to solve existing issues.

E E 559 Special Topics in Electrical Energy Systems (1-5, max. 16)
Topics of current interest in electrical power and energy devices and systems. Content varies from year to year, based on current professional interests of faculty member in charge.

E E 560 Neural Engineering (3)
Introduces the field of Neural Engineering: overview of neurobiology, recording and stimulating the nervous system, signal processing, machine learning, powering and communicating with neural devices, invasive and non-invasive brain-machine interfaces, spinal interfaces, smart prostheses, deep-brain stimulators, cochlear implants and neuroethics. Heavy emphasis on primary literature. Offered: jointly with BIOEN 560; A.

E E 561 Neural Engineering Tech Studio (4)
Neural engineering design and translational engineering. Groups design, build and present a neural engineering prototype project to a panel of industry judges. Prerequisite: BIOEN 560 Offered: jointly with BIOEN 561; W.

E E 562 Artificial Intelligence for Engineers (3)
Covers main areas of artificial intelligence (AI) without need for extensive prerequisites. Programming languages for AI; problem solving; representations; control strategies; searching strategies; predicate calculus; rule-based deduction; goal-directed planning; knowledge-based systems. Prerequisite: CSE 373.

E E 563 Submodular Functions, Optimization, and Applications (4)
Submodularity and supermodularity. Definitions, properties, operations that preserve submodularity, variants, certain special submodular functions, computational properties, matroids and lattices, polyhedral properties, semidifferentials, convex/concave extensions, constrained and unconstrained minimization and maximization, and generalizations of submodularity and uses in machine learning. Prerequisite: E E 510/A A 510/CHEM E 510/M E 510. Offered: even years.

E E 564 Neural Computation and Engineering Laboratory (4)
Introduces neural recording and quantitative analysis techniques to students with a background in quantitative methods. Offered: jointly with BIOEN 566.

E E 565 Computer-Communication Networks I (4)
Network architectures and protocols; layered model; reliable transmission protocols at the data control layer; Transmission Control Protocols (TCP); routing algorithms; performance modeling, and analysis of packet-switched networks. Multi-access. Projects involving routing and multi-access principles. Prerequisite: E E 505.

E E 568 Digital Image Processing (4)
Digital image processing techniques and various special topics such as image restoration, image segmentation, multi-resolution imaging with wavelet transform, and image registration. Prerequisite: permission of instructor.

E E 569 Advanced Neurotechnology (3)
Seminar explores the current and future challenges in neural engineering such as consumer and medical devices to augment and enhance function such as learning and memory, brain-computer interfaces, and neural stimulation. Prerequisite: BIOEN 460/E E 460 or BIOEN 560/E E 560. Offered: Sp.

E E 572 Electromagnetics I: Microwave Engineering (4)
Covers microwave transmission line models and their applications; electromagnetic waves in layered media; mode structures in metallic and dielectric waveguides; resonators and cavities; and Green's functions. Course overlaps with: TECE 572. Prerequisite: E E 361.

E E 574 Antennas: Analysis and Design (4)
Covers fundamentals of antennas, analysis, synthesis, and computer-aided design; applications in communications, remote sensing, and radars; radiation pattern; directivity; impedance; wire antennas; arrays; numerical methods for analysis; horn antennas; microstrip antennas; and reflector antennas.

E E 575 Radar Remote Sensing (4)
Introduces radar remote sensing. Covers the fundamentals of radar systems, monostatic and bistatic topologies, radar equation, range-time diagram; ambiguity function, pulse compression, elementary estimation and detection theory, spectrum estimation for underspread and overspread targets; interferometry, source imaging; and Time Difference of Arrival, Aperture Synthesis (SAR and ISAR).

E E 576 Computer Vision (3)
Principles and methods for interpreting the three-dimensional world from images. Topics include feature detection, image segmentation, motion estimation, image mosaics, 3D-shape reconstruction, object recognition, and image retrieval. Prerequisite: solid knowledge of linear algebra; good programming skills. Offered: jointly with CSE 576.

E E 577 Special Topics in Computer Vision (3)
Topics vary and may include vision for graphics, probabilistic vision and learning, medical imaging, content-based image and video retrieval, robot vision, or 3D object recognition. Prerequisite: CSE 576/E E 576. Offered: jointly with CSE 577.

E E 578 Convex Optimization (4)
Basics of convex analysis: Convex sets, functions, and optimization problems. Optimization theory: Least-squares, linear, quadratic, geometric and semidefinite programming. Convex modeling. Duality theory. Optimality and KKT conditions. Applications in signal processing, statistics, machine learning, control communications, and design of engineering systems. Prerequisite: A A 510, CHEM E 510, E E 510, or M E 510. Offered: jointly with A A 578/CSE 578/M E 578.

E E 579 Advanced Topics in Electromagnetics, Optics, and Acoustics (1-5, max. 16)
Topics of current interest in electromagnetics, optics, and acoustics. Content varies from year to year, based on current professional interests of faculty member in charge.

E E 580 Geometric Methods for Non-Linear Control Systems (3)
Analysis and design of nonlinear control systems focusing on differential geometric methods. Topics include controllability, observability, feedback linearization, invariant distributions, and local coordinate transformations. Emphasis on systems evolving on Lie groups and linearly uncontrollable systems. Offered: jointly with A A 580/M E 580; Sp, even years.

E E 581 Digital Control System Design (4)
Digital control system design by classical methods. Discrete-time systems and the z-transform. Modeling sampled-data systems. Frequency response of discrete time systems and aliasing. Nyquist stability criterion and gain and phase margins. Discrete-time control law determination by direct z-plane root locus and loop shaping methods. Includes hands-on-with-hardware projects. Course overlaps with: TECE 553. Prerequisite: AA/EE 447 or ME 471. Offered: jointly with A A 581/M E 581; W.

E E 582 Introduction to Discrete Event Systems (3)
Modeling DES with automata and Petri nets. Languages. State estimation and diagnostics. Control specifications. Feedback control. Dealing with uncontrollability and unobservability. Dealing with blocking. Timed automata and Petri nets. Prerequisite: A A 447/E E 447/ M E 471. Offered: jointly with A A 582/M E 582; Sp, even years.

E E 583 Nonlinear Control Systems (3)
Analysis of nonlinear systems and nonlinear control system design. Phase plane analysis. Lyapunov stability analysis. Describing functions. Feedback linearization. Introduction to variable structure control. Course overlaps with: TECE 551 and TECE 555. Prerequisite: A A 447/E E 447/M E 471. Offered: jointly with A A 583/M E 583.

E E 584 Sensors and Sensor Systems (4)
Introduction to optical and solid-state chemical and physical sensors. Topics include transduction mechanisms, design parameters, fabrication methods and applications. Prerequisite: E E 331.

E E 585 System Identification and Adaptive Control (3)
Theory and methods of system identification and adaptive control. Identification of linear-in-parameter systems, using recursive LS and extended LS methods; model order selection. Indirect and direct adaptive control. Controller synthesis, transient and stability properties. Offered: jointly with A A 585/M E 585.

E E 586 Digital Video Coding Systems (4)
Introduction to digital video coding algorithms and systems. Theoretical and practical aspects of important topics on digital video coding algorithms, motion estimation, video coding standards, systems issues, and visual communications.

E E 587 Introduction to Photonics (4)
Introduction to optical principles and phenomena. Topics include electromagnetic theory of light, optical interference, diffraction, polarization, optical waveguides, and optical fibers. Prerequisite: either EE 361, PHYS 123, or PHYS 143; recommended: basic principles of electromagnetism; complex numbers and functions; introductory differential and integral calculus; linear differential equations.

E E 588 Advanced Photonics (4)
In-depth understanding and learning of advanced subjects in photonics. Topics include optical resonance, quantum nature of light and optical transitions, optical amplification, laser operation, and photodetection. Prerequisite: either E E 485, E E 487, or E E 587.

E E 589 Advanced Topics in Sensors and Sensor Systems (3)
Topics of current interest in sensors and sensor systems.

E E 590 Advanced Topics in Digital Computers (2-5, max. 16)
Lectures or discussions of topics of current interest in the field of digital systems. Subject matter may vary from year to year.

E E 591 Robotics and Control Systems Colloquium (1, max. 30)
Colloquium on current topics in robotics and control systems analysis and design. Topics presented by invited speakers as well as on-campus speakers. Emphasis on the cross-disciplinary nature of robotics and control systems. Credit/no-credit only. Offered: jointly with A A 591/CHEM E 591/M E 591.

E E 593 Feedforward Control (3)
Design feedforward controllers for precision output tracking; inversion-based control of non-minimum-phase systems; effect of plant uncertainty on feedforward control; design of feedforward controllers for applications such as vertical take off and landing aircraft, flexible structures and piezo-actuators. Prerequisite: A A 547/E E 547/M E 547. Offered: jointly with A A 593/M E 593; Sp, even years.

E E 594 Robust Control (3)
Basic foundations of linear analysis and control theory, model realization and reduction, balanced realization and truncation, stabilization problem, coprime factorizations, Youla parameterization, matrix inequalities, H-infinity and H2 control, KYP lemma, uncertain systems, robust H2, integral quadratic constraints, linear parameter varying synthesis, applications of robust control. Prerequisite: A A 547/E E 547/M E 547. Offered: jointly with A A 594/M E 594; Sp, odd years.

E E 595 Advanced Topics in Communication Theory (1-5, max. 16)
Extension of E E 507, E E 508, E E 518, E E 519, E E 520. Material differs each year, covering such topics as: detection theory, decision theory, game theory, adaptive communication systems, nonlinear random processes.

E E 596 Advanced Topics in Signal and Image Processing (2-5, max. 16)
Topics of current interest in signal and image processing. Content may vary from offering to offering.

E E 597 Networked Dynamics Systems (3)
Provides an overview of graph-theoretic techniques that are instrumental for studying dynamic systems that coordinate their states over a signal-exchange network. Topics include network models, network properties, dynamics over networks, formation control, biological networks, observability, controllability, and performance measures over networks. Prerequisite: A A 547/E E 547/M E 547. Offered: jointly with A A 597/M E 597.

E E 598 Special topics in Electrical Engineering (1-5, max. 16)
Topics of current interest in non-traditional areas of electrical engineering.

E E 599 Special Projects in Electrical Engineering (1-5, max. 15)
Prerequisite: permission of instructor.

E E 600 Independent Study or Research (*-)

E E 700 Master's Thesis (*-)

E E 800 Doctoral Dissertation (*-)