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11 - 20 of 62 results for: EE ; Currently searching spring courses. You can expand your search to include all quarters

EE 157: Electric Motors for Renewable Energy, Robotics, and Electric Vehicles

An introduction to electric motors and the principles of electromechanical energy conversion. Students will learn about, design, and build an electric motor system, choosing from one of three application areas: renewable energy (wind turbines), robotics (drones and precision manufacturing), or electric vehicles (cars, ships, and airplanes). Topics covered include ac and dc rotating machines, power electronics inverters and drives, and control techniques. Prerequisite: EE 42, Physics 43, ENGR 40M or equivalent.
Terms: Spr | Units: 3

EE 178: Probabilistic Systems Analysis

Introduction to probability and its role in modeling and analyzing real world phenomena and systems, including topics in statistics, machine learning, and statistical signal processing. Elements of probability, conditional probability, Bayes rule, independence. Discrete and continuous random variables. Signal detection. Functions of random variables. Expectation; mean, variance and covariance, linear MSE estimation. Conditional expectation; iterated expectation, MSE estimation, quantization and clustering. Parameter estimation. Classification. Sample averages. Inequalities and limit theorems. Confidence intervals. Prerequisites: Calculus at the level of MATH 51, CME 100 or equivalent and basic knowledge of computing at the level of CS106A.
Terms: Spr | Units: 3-4 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR

EE 190: Special Studies or Projects in Electrical Engineering

Independent work under the direction of a faculty member. Individual or team activities involve lab experimentation, design of devices or systems, or directed reading. Course may be repeated for credit.
Terms: Aut, Win, Spr, Sum | Units: 1-15 | Repeatable for credit
Instructors: Arbabian, A. (PI) ; Bambos, N. (PI) ; Boahen, K. (PI) ; Boneh, D. (PI) ; Bowden, A. (PI) ; Boyd, S. (PI) ; Cioffi, J. (PI) ; Clark, S. (PI) ; Dally, B. (PI) ; Duchi, J. (PI) ; El Gamal, A. (PI) ; Emami-Naeini, A. (PI) ; Engler, D. (PI) ; Fan, J. (PI) ; Fan, S. (PI) ; Fraser-Smith, A. (PI) ; Gibbons, J. (PI) ; Giovangrandi, L. (PI) ; Girod, B. (PI) ; Hanrahan, P. (PI) ; Hennessy, J. (PI) ; Hesselink, L. (PI) ; Horowitz, M. (PI) ; Howe, R. (PI) ; Inan, U. (PI) ; Kahn, J. (PI) ; Kapetanovic, Z. (PI) ; Katti, S. (PI) ; Kazovsky, L. (PI) ; Khuri-Yakub, B. (PI) ; Kovacs, G. (PI) ; Kozyrakis, C. (PI) ; Lall, S. (PI) ; Lee, T. (PI) ; Levis, P. (PI) ; Levoy, M. (PI) ; McKeown, N. (PI) ; Miller, D. (PI) ; Mitchell, J. (PI) ; Mitra, S. (PI) ; Montanari, A. (PI) ; Murmann, B. (PI) ; Nishi, Y. (PI) ; Nishimura, D. (PI) ; Olukotun, O. (PI) ; Osgood, B. (PI) ; Paulraj, A. (PI) ; Pauly, J. (PI) ; Pease, R. (PI) ; Pianetta, P. (PI) ; Plummer, J. (PI) ; Poon, A. (PI) ; Pop, E. (PI) ; Prabhakar, B. (PI) ; Rivas-Davila, J. (PI) ; Rosenblum, M. (PI) ; Saraswat, K. (PI) ; Schroeder, D. (PI) ; Senesky, D. (PI) ; Soh, H. (PI) ; Solgaard, O. (PI) ; Song, S. (PI) ; Thompson, N. (PI) ; Thrun, S. (PI) ; Tobagi, F. (PI) ; Van Roy, B. (PI) ; Vuckovic, J. (PI) ; Wang, S. (PI) ; Weissman, T. (PI) ; Wetzstein, G. (PI) ; Widom, J. (PI) ; Widrow, B. (PI) ; Wong, H. (PI) ; Wong, S. (PI) ; Wooley, B. (PI) ; Wootters, M. (PI) ; Yamamoto, Y. (PI) ; Zebker, H. (PI)

EE 191: Special Studies and Reports in Electrical Engineering

Independent work under the direction of a faculty member given for a letter grade only. If a letter grade given on the basis of required written report or examination is not appropriate, enroll in 190. Course may be repeated for credit.
Terms: Aut, Win, Spr, Sum | Units: 1-15 | Repeatable for credit

EE 191A: Special Studies and Reports in Electrical Engineering

Terms: Aut, Win, Spr | Units: 1

EE 191W: Special Studies and Reports in Electrical Engineering (WIM)

WIM-version of EE 191. For EE students using special studies (e.g., honors project, independent research project) to satisfy the writing-in-major requirement. A written report that has gone through revision with an adviser is required. An adviser from the Technical Communication Program is recommended.
Terms: Aut, Win, Spr, Sum | Units: 3-10

EE 195: Electrical Engineering Instruction

Terms: Aut, Win, Spr | Units: 1-3

EE 207: Neuromorphics: Brains in Silicon (BIOE 313)

While traversing through the natural world, you effortlessly perceive and react to a rich stream of stimuli. This constantly changing stream evokes spatiotemporal patterns of spikes that propagate through your brain from one ensemble of neurons to another. An ensemble may memorize a spatiotemporal pattern at the speed of life and recall it at the speed of thought. In the first half of this course, we will discuss and model how a neural ensemble memorizes and recalls such a spatiotemporal pattern. In the second half, we will explore how neuromorphic hardware could exploit these neurobiological mechanisms to run AI not with megawatts in the cloud but rather with watts on a smartphone. Prerequisites: Either computational modeling ( BIOE 101, BIOE 300B) or circuit analysis ( EE 101A).
Terms: Spr | Units: 3
Instructors: Boahen, K. (PI)

EE 219: 3D+ Imaging Sensors (EE 119)

Formally EE 292Q. Introduction to operation principles and key performance aspects of 3D+ imaging sensors used widely in industry. Concepts include imaging physics, data acquisition and image formation methods, and signal and image quality metrics that are broadly applicable across sensor types. Practical examples and demonstrations of various sensors such as radar, acoustic, LIDAR, and ToF modules will be presented in class as well as through structured labs. Invited speakers will highlight emerging 3D+ imaging applications that these sensors are enabling today. Prerequisites: EE 101A or equivalent. EE 102A or equivalent.
Terms: Spr | Units: 3

EE 224: Quantum Control and Engineering

Introduction to quantum control, dynamics, and information processing, aimed at graduate students and advanced undergraduate students. Prerequisites include knowledge of quantum mechanics, linear algebra, and statistical analysis. The course will provide an overview of both the fundamentals and state-of-the-art techniques in the area of quantum engineering. Topics include qubits and operators, modeling and numerical analysis of open quantum systems, quantum control protocols, average Hamiltonian theory, dynamical decoupling, quantum device benchmarking, different quantum platforms and their applications.
Terms: Spr | Units: 3
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