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EE 1
The Science of Data, Signals, and Information
9 units (306)

third term
Electrical Engineering has given rise to many key developments at the interface between the physical world and the information world. Fundamental ideas in data acquisition, sampling, signal representation, and quantification of information have their origin in electrical engineering.This course introduces these ideas and discusses signal representations, the interplay between time and frequency domains, difference equations and filtering, noise and denoising, data transmission over channels with limited capacity, signal quantization, feedback and neural networks, and how humans interpret data and information. Applications in various areas of science and engineering are covered. Satisfies the menu requirement of the Caltech core curriculum.
Instructor:
Vaidyanathan
EE 2
Electrical Engineering Entrepreneurial and Research Seminar
1 unit

second term
Required for EE undergraduates. Weekly seminar given by successful entrepreneurs and EE faculty, broadly describing their path to success and introducing different areas of research in electrical engineering: circuits and VLSI, communications, control, devices, images and vision, information theory, learning and pattern recognition, MEMS and micromachining, networks, electromagnetics and optoelectronics, RF and microwave circuits and antennas, robotics and signal processing, specifically, research going on at Caltech and in the industry.
Instructor:
Emami
FS/EE 5
Introduction to Waves
6 units (150)

first term
This course is an intuitive introduction to waves. Have you ever wanted to break a wineglass with sound? Or make your own hologram? Or stand under a powerline with a fluorescent light tube? Ever wondered what a soliton wave or a vortex is? Come do this and more, as we dissect various types of wave phenomena mathematically and then see them in action with your own experiments.
Instructor:
Yang
EE/ME 7
Introduction to Mechatronics
6 units (231)

first term
Mechatronics is the multidisciplinary design of electromechanical systems. This course is intended to give the student a basic introduction to such systems. The course will focus on the implementations of sensor and actuator systems, the mechanical devices involved and the electrical circuits needed to interface with them. The class will consist of lectures and short labs where the student will be able to investigate the concepts discussed in lecture. Topics covered include motors, piezoelectric devices, light sensors, ultrasonic transducers, and navigational sensors such as accelerometers and gyroscopes. Graded pass/fail. Not Offered 202021.
Instructor:
George
APh/EE 9 ab
SolidState Electronics for Integrated Circuits
6 units (222)

first, third terms
Prerequisites: Successful completion of APh/EE 9 a is a prerequisite for enrollment in APh/EE 9 b.
Introduction to solidstate electronics, including physical modeling and device fabrication. Topics: semiconductor crystal growth and device fabrication technology, carrier modeling, doping, generation and recombination, pn junction diodes, MOS capacitor and MOS transistor operation, and deviations from ideal behavior. Laboratory includes computeraided layout, and fabrication and testing of lightemitting diodes, transistors, and inverters. Students learn photolithography, and use of vacuum systems, furnaces, and devicetesting equipment. APh/EE 9b not offered 202021.
Instructor:
Scherer
EE/CS 10 ab
Introduction to Digital Logic and Embedded Systems
6 units (231)

second, third terms
This course is intended to give the student a basic understanding of the major hardware and software principles involved in the specification and design of embedded systems. The course will cover basic digital logic, programmable logic devices, CPU and embedded system architecture, and embedded systems programming principles (interfacing to hardware, events, user interfaces, and multitasking).
Instructor:
George
EE 13
Electronic System Prototyping
3 units (030)

first term
This course is intended to introduce the student to the technologies and techniques used to fabricate electronic systems. The course will cover the skills needed to use standard CAD tools for circuit prototyping. This includes schematic capture and printed circuit board design. Additionally, soldering techniques will be covered for circuit fabrication as well as some basic debugging skills. Each student will construct a system from schematic to PCB to soldering the final prototype. Not Offered 202021.
Instructor:
George
APh/EE 23
Demonstration Lectures in Classical and Quantum Photonics
9 units (306)

first term
Prerequisites: Ph 1 abc.
This course covers fundamentals of photonics with emphasis on modern applications in classical and quantum optics. Classical optical phenomena including interference, dispersion, birefringence, diffraction, laser oscillation, and the applications of these phenomena in optical systems employing multiplebeam interferometry, Fouriertransform image processing, holography, electrooptic modulation, optical detection and heterodyning will be covered. Quantum optical phenomena like single photon emission will be discussed. Examples will be selected from optical communications, radar, adaptive optical systems, nanophotonic devices and quantum communications. Prior knowledge of quantum mechanics is not required.
Instructor:
Faraon
APh/EE 24
Introductory Optics and Photonics Laboratory
9 units (135)

second term
Prerequisites: APh 23.
Laboratory experiments to acquaint students with the contemporary aspects of optics and photonics research and technology. Experiments encompass many of the topics and concepts covered in APh 23.
Instructor:
Faraon
EE 40
Physics of Electrical Engineering
9 units (306)

third term
This course provides an introduction to the fundamental physics of modern device technologies in electrical engineering used for sensing, communications, computing, imaging, and displays. The course overviews topics including semiconductor physics, quantum mechanics, electromagnetics, and optics with emphasis on physical operation principles of devices. Example technologies include integrated circuits, optical and wireless communications, micromechanical systems, lasers, highresolution displays, LED lighting, and imaging.
Instructor:
Marandi
EE 44
Deterministic Analysis of Systems and Circuits
12 units (408)

first term
Prerequisites: Ph 1 abc, can be taken concurrently with Ma 2 and Ph 2 a.
Modeling of physical systems by conversion to mathematical abstractions with an emphasis on electrical systems. Introduction to deterministic methods of system analysis, including matrix representations, timedomain analysis using impulse and step responses, signal superposition and convolution, Heaviside operator solutions to systems of linear differential equations, transfer functions, Laplace and Fourier transforms. The course emphasizes examples from the electrical circuits (e.g., energy and data converters, wired and wireless communication channels, instrumentation, and sensing) , while providing some exposure to other selected applications of the deterministic analysis tool (e.g., public opinion, acoustic cancellation, financial markets, traffic, drug delivery, mechanical systems, news cycles, and heat exchange).
Instructor:
Hajimiri
EE 45
Electronics Systems and Laboratory
12 units (336)

second term
Prerequisites: EE 44.
Fundamentals of electronic circuits and systems. Lectures on diodes, transistors, smallsignal analysis, frequency domain analysis, application of Laplace transform, gain stages, differential signaling, operational amplifiers, introduction to radio and analog communication systems. Laboratory sessions on transient response, steadystate sinusoidal response and phasors, diodes, transistors, amplifiers.
Instructor:
Emami
EE 55
Mathematics of Electrical Engineering
9 units (306)

first term
Prerequisites: Ma 1abc.
Linear algebra and probability are fundamental to many areas of study in electrical engineering. This class provides the mathematical foundations of these topics with a view to their utility to electrical engineers. Topics include vector spaces, matrices and linear transformations, the singular value decomposition, elementary probability and random variables, common distributions that arise in electrical engineering, and datafitting. Connections to signal processing, systems, communications, optimization, and machine learning are highlighted.
Instructor:
Chandrasekaran
CS/EE/ME 75 abc
Multidisciplinary Systems Engineering
3 units (201), 6 units (204), or 9 units (207) first term; 6 units (231), 9 units (261), or 12 units (291) second and third terms; units according to project selected

first, second, third terms
This course presents the fundamentals of modern multidisciplinary systems engineering in the context of a substantial design project. Students from a variety of disciplines will conceive, design, implement, and operate a system involving electrical, information, and mechanical engineering components. Specific tools will be provided for setting project goals and objectives, managing interfaces between component subsystems, working in design teams, and tracking progress against tasks. Students will be expected to apply knowledge from other courses at Caltech in designing and implementing specific subsystems. During the first two terms of the course, students will attend project meetings and learn some basic tools for project design, while taking courses in CS, EE, and ME that are related to the course project. During the third term, the entire team will build, document, and demonstrate the course design project, which will differ from year to year. Freshmen must receive permission from the lead instructor to enroll. Not offered 202021.
EE 80 abc
Senior Thesis
9 units

first, second, third terms
Prerequisites: instructor's permission, which should be obtained during the junior year to allow sufficient time for planning the research.
Individual research project, carried out under the supervision of a member of the electrical engineering or computer science faculty. Project must include significant design effort. Written report required. Open only to senior electrical engineering, computer science, or electrical and computer engineering majors. Not offered on a pass/fail basis.
Instructor:
Staff
EE 90
Analog Electronics Project Laboratory
9 units (180)

third term
Prerequisites: EE 40 and EE 45.
A structured laboratory course that gives the student the opportunity to design and build a simple analog electronics project. The goal is to gain familiarity with circuit design and construction, component selection, CAD support, and debugging techniques.
Instructor:
Ohanian
EE 91 ab
Experimental Projects in Electronic Circuits
9 units (180)

first, second terms
Prerequisites: EE 45. Recommended: EE/CS 10 ab, and EE/MedE 114 ab (may be taken concurrently). Open to seniors; others only with instructor's permission.
An opportunity to do advanced original projects in analog or digital electronics and electronic circuits. Selection of significant projects, the engineering approach, modern electronic techniques, demonstration and review of a finished product. DSP/microprocessor development support and analog/digital CAD facilities available.
Instructor:
Ohanian
EE 99
Advanced Work in Electrical Engineering
Units to be arranged
Special problems relating to electrical engineering will be arranged. For undergraduates; students should consult with their advisers. Graded pass/fail.
EE 105 abc
Electrical Engineering Seminar
1 unit

first, second, third terms
All candidates for the M.S. degree in electrical engineering are required to attend any graduate seminar in any division each week of each term. Graded pass/fail.
Instructor:
Emami
ACM/EE 106 ab
Introductory Methods of Computational Mathematics
12 units (309)

first, second terms
Prerequisites: Ma 1 abc, Ma 2, Ma 3, ACM 11, ACM 95/100 ab or equivalent.
The sequence covers the introductory methods in both theory and implementation of numerical linear algebra, approximation theory, ordinary differential equations, and partial differential equations. The linear algebra parts covers basic methods such as direct and iterative solution of large linear systems, including LU decomposition, splitting method (Jacobi iteration, GaussSeidel iteration); eigenvalue and vector computations including the power method, QR iteration and Lanczos iteration; nonlinear algebraic solvers. The approximation theory includes data fitting; interpolation using Fourier transform, orthogonal polynomials and splines; least square method, and numerical quadrature. The ODE parts include initial and boundary value problems. The PDE parts include finite difference and finite element for elliptic/parabolic/hyperbolic equation. Stability analysis will be covered with numerical PDE. Programming is a significant part of the course.
Instructor:
Hou
APh/EE 109
Introduction to the Micro/Nanofabrication Lab
9 units (063)

first, second, third terms
Introduction to techniques of microand nanofabrication, including solidstate, optical, and microfluidic devices. Students will be trained to use fabrication and characterization equipment available in the applied physics micro and nanofabrication lab. Topics include Schottky diodes, MOS capacitors, lightemitting diodes, microlenses, microfluidic valves and pumps, atomic force microscopy, scanning electron microscopy, and electronbeam writing.
Instructors:
Troian, Ghaffari
EE 110 abc
Embedded Systems Design Laboratory
9 units (342)

first, second, third terms
The student will design, build, and program a specified microprocessorbased embedded system. This structured laboratory is organized to familiarize the student with largescale digital and embedded system design, electronic circuit construction techniques, modern development facilities, and embedded systems programming. The lectures cover topics in embedded system design such as display technologies, interfacing to analog signals, communication protocols, PCB design, and programming in highlevel and assembly languages. Given in alternate years; 110 c Offered 202021; 110 ab Not offered 202021.
Instructor:
George
EE 111
SignalProcessing Systems and Transforms
9 units (306)

first term
Prerequisites: Ma 1.
An introduction to continuous and discrete time signals and systems with emphasis on digital signal processing systems. Study of the Fourier transform, Fourier series, ztransforms, and the fast Fourier transform as applied in electrical engineering. Sampling theorems for continuous to discretetime conversion. Difference equations for digital signal processing systems, digital system realizations with block diagrams, analysis of transient and steady state responses, and connections to other areas in science and engineering.
Instructor:
Vaidyanathan
EE 112
Introduction to Signal Processing from Data
9 units (306)

second term
Prerequisites: EE 111 or equivalent. Math 3 recommended.
Fundamentals of digital signal processing, extracting information from data by linear filtering, recursive and nonrecursive filters, structural and flow graph representations for filters, dataadaptive filtering, multrirate sampling, efficient data representations with filter banks, Nyquist and subNyquist sampling, sensor array signal processing, estimating direction of arrival (DOA) information from noisy data, and spectrum estimation. Not Offered 202021.
Instructor:
Vaidyanathan
EE 113
Feedback and Control Circuits
9 units (333)

third term
Prerequisites: EE 45 or equivalent.
This class studies the design and implementation of feedback and control circuits. The course begins with an introduction to basic feedback circuits, using both op amps and transistors. These circuits are used to study feedback principles, including circuit topologies, stability, and compensation. Following this, basic control techniques and circuits are studied, including PID (ProportionalIntegratedDerivative) control, digital control, and fuzzy control. There is a significant laboratory component to this course, in which the student will be expected to design, build, analyze, test, and measure the circuits and systems discussed in the lectures.
Instructor:
George
EE/MedE 114 ab
Analog Circuit Design
12 units (408)

second, third terms
Prerequisites: EE 44 or equivalent.
Analysis and design of analog circuits at the transistor level. Emphasis on designoriented analysis, quantitative performance measures, and practical circuit limitations. Circuit performance evaluated by hand calculations and computer simulations. Recommended for juniors, seniors, and graduate students. Topics include: review of physics of bipolar and MOS transistors, lowfrequency behavior of singlestage and multistage amplifiers, current sources, active loads, differential amplifiers, operational amplifiers, highfrequency circuit analysis using time and transfer constants, highfrequency response of amplifiers, feedback in electronic circuits, stability of feedback amplifiers, and noise in electronic circuits, and supply and temperature independent biasing. A number of the following topics will be covered each year: translinear circuits, switched capacitor circuits, data conversion circuits (A/D and D/A), continuoustime Gm.C filters, phase locked loops, oscillators, and modulators. Offered 202021.
Instructor:
Hajimiri
EE/MedE 115
Micro/Nanoscales ElectroOptics
9 units (306)

first term
Prerequisites: Introductory electromagnetic class and consent of the instructor.
The course will cover various electrooptical phenomena and devices in the micro/nanoscales. We will discuss basic properties of light, imaging, aberrations, eyes, detectors, lasers, microoptical components and systems, scalar diffraction theory, interference/interferometers, holography, dielectric/plasmonic waveguides, and various Raman techniques. Topics may vary. Not offered 202021.
ACM/EE/IDS 116
Introduction to Probability Models
9 units (315)

first term
Prerequisites: Ma 3, some familiarity with MATLAB, e.g. ACM 11 is desired.
This course introduces students to the fundamental concepts, methods, and models of applied probability and stochastic processes. The course is application oriented and focuses on the development of probabilistic thinking and intuitive feel of the subject rather than on a more traditional formal approach based on measure theory. The main goal is to equip science and engineering students with necessary probabilistic tools they can use in future studies and research. Topics covered include sample spaces, events, probabilities of events, discrete and continuous random variables, expectation, variance, correlation, joint and marginal distributions, independence, moment generating functions, law of large numbers, central limit theorem, random vectors and matrices, random graphs, Gaussian vectors, branching, Poisson, and counting processes, general discrete and continuoustimed processes, auto and crosscorrelation functions, stationary processes, power spectral densities.
Instructor:
Zuev
ME/EE/EST 117
Energy Technology and Policy
9 units (306)

first term
Prerequisites: Ph 1 abc, Ch 1 ab and Ma 1 abc.
Energy technologies and the impact of government policy. Fossil fuels, nuclear power, and renewables for electricity production and transportation. Resource models and climate change policies. New and emerging technologies.
Instructor:
Blanquart
Ph/APh/EE/BE 118 abc
Physics of Measurement
9 units (306)

second, third terms
Prerequisites: Ph 127, APh 105, or equivalent, or permission from instructor.
This course focuses on exploring the fundamental underpinnings of experimental measurements from the perspectives of responsivity, noise, backaction, and information. Its overarching goal is to enable students to critically evaluate real measurement systems, and to determine the ultimate fundamental and practical limits to information that can be extracted from them. Topics will include physical signal transduction and responsivity, fundamental noise processes, modulation, frequency conversion, synchronous detection, signalsampling techniques, digitization, signal transforms, spectral analyses, and correlations. The first term will cover the essential fundamental underpinnings, while topics in second term will include examples from optical methods, highfrequency and fast temporal measurements, biological interfaces, signal transduction, biosensing, and measurements at the quantum limit. Part c not offered in 202021.
Instructor:
Roukes
EE/CS 119 abc
Advanced Digital Systems Design
9 units (333)

first, second terms
Prerequisites: EE/CS 10 a or CS 24.
Advanced digital design as it applies to the design of systems using PLDs and ASICs (in particular, gate arrays and standard cells). The course covers both design and implementation details of various systems and logic device technologies. The emphasis is on the practical aspects of ASIC design, such as timing, testing, and fault grading. Topics include synchronous design, state machine design, ALU and CPU design, applicationspecific parallel computer design, design for testability, PALs, FPGAs, VHDL, standard cells, timing analysis, fault vectors, and fault grading. Students are expected to design and implement both systems discussed in the class as well as selfproposed systems using a variety of technologies and tools. Given in alternate years; Offered 202021.
Instructor:
George
EE/APh 120
Physical Optics
9 units (306)

second term
Prerequisites: Intermediatelevel familiarity with Fourier transforms and linear systems analysis. Basic familiarity with Maxwell's electromagnetic theory (EE40 and EE44, or equivalent).
Course focuses on applying linear systems analysis on propagation of light waves. Contents begin with a review of Electromagnetic theory of diffraction and transitions to Fourier Optics for a scalarwave treatment of propagation, diffraction, and image formation with coherent and incoherent light. In addition to problems in imaging, the course makes connections to a selected number of topics in optics where the mathematics of wave phenomena plays a central role. Examples include propagation of light in multilayer films and meta surfaces, Gaussian beams, FabryPÃƒÂ©rot cavities, and angular momentum of light. Areas of application include modern imaging, display, and beam shaping technologies.
Instructor:
Mirhosseini
EE 121
Computational Signal Processing
12 units (309)

first term
Prerequisites: EE 111, ACM/EE/IDS 116, ACM/IDS 104.
The role of computation in the acquisition, representation, and processing of signals. The course develops methodology based on linear algebra and optimization, with an emphasis on the interplay between structure, algorithms, and accuracy in the design and analysis of the methods. Specific topics covered include deterministic and stochastic signal models, statistical signal processing, inverse problems, and regularization. Problems arising in contemporary applications in the sciences and engineering are discussed, although the focus is on the common abstractions and methodological frameworks that are employed in the solution of these problems. Not offered 202021.
Instructor:
Chandrasekaran
EE/APh 123
Advanced Lasers and Photonics Laboratory
9 units (135)

first term
Prerequisites: none.
This course focuses on handson experience with advanced techniques related to lasers, optics, and photonics. Students have the opportunity to build and run several experiments and analyze data. Covered topics include laserbased microscopy, spectroscopy, nonlinear optics, quantum optics, ultrafast optics, adaptive optics, and integrated photonics. Limited enrollment. Not offered 202021.
Instructor:
Marandi
EE/MedE 124
Mixedmode Integrated Circuits
9 units (306)

third term
Prerequisites: EE 45 a or equivalent.
Introduction to selected topics in mixedsignal circuits and systems in highly scaled CMOS technologies. Design challenges and limitations in current and future technologies will be discussed through topics such as clocking (PLLs and DLLs), clock distribution networks, sampling circuits, highspeed transceivers, timing recovery techniques, equalization, monitor circuits, power delivery, and converters (A/D and D/A). A design project is an integral part of the course.
Instructor:
Emami
EE/CS/MedE 125
Digital Electronics and Design with FPGAs and VHDL
9 units (360)

third term
Prerequisites: basic knowledge of digital electronics.
Study of programmable logic devices (CPLDs and FPGAs). Detailed study of the VHDL language, with basic and advanced applications. Review and discussion of digital design principles for combinationallogic, combinationalarithmetic, sequential, and statemachine circuits. Detailed tutorials for synthesis and simulation tools using FPGAs and VHDL. Wide selection of complete, realworld fundamental advanced projects, including theory, design, simulation, and physical implementation. All designs are implemented using stateoftheart development boards. Offered 202021.
Instructor:
Pedroni
EE/Ma/CS 126 ab
Information Theory
9 units (306)

first, second terms
Prerequisites: Ma 3.
Shannon's mathematical theory of communication, 1948present. Entropy, relative entropy, and mutual information for discrete and continuous random variables. Shannon's source and channel coding theorems. Mathematical models for information sources and communication channels, including memoryless, Markov, ergodic, and Gaussian. Calculation of capacity and ratedistortion functions. Universal source codes. Side information in source coding and communications. Network information theory, including multiuser data compression, multiple access channels, broadcast channels, and multiterminal networks. Discussion of philosophical and practical implications of the theory. This course, when combined with EE 112, EE/Ma/CS/IDS 127, EE/CS 161, and EE/CS/IDS 167, should prepare the student for research in information theory, coding theory, wireless communications, and/or data compression.
Instructor:
Effros
EE/Ma/CS/IDS 127
ErrorCorrecting Codes
9 units (306)

second term
Prerequisites: Ma 2.
This course develops from first principles the theory and practical implementation of the most important techniques for combating errors in digital transmission or storage systems. Topics include algebraic block codes, e.g., Hamming, BCH, ReedSolomon (including a selfcontained introduction to the theory of finite fields); and the modern theory of sparse graph codes with iterative decoding, e.g. LDPC codes, turbo codes. The students will become acquainted with encoding and decoding algorithms, design principles and performance evaluation of codes. Not Offered 202021.
Instructor:
Kostina
EE 128 ab
Selected Topics in Digital Signal Processing
9 units (306)

second, third terms
Prerequisites: EE 111 and EE/CS/IDS 160 or equivalent required, and EE 112 or equivalent recommended.
The course focuses on several important topics that are basic to modern signal processing. Topics include multirate signal processing material such as decimation, interpolation, filter banks, polyphase filtering, advanced filtering structures and nonuniform sampling, optimal statistical signal processing material such as linear prediction and antenna array processing, and signal processing for communication including optimal transceivers. Not offered 202021.
ME/CS/EE 129
Experimental Robotics
9 units (360)

first term
This course covers the foundations of experimental realization on robotic systems. This includes software infrastructures, e.g., robotic operating systems (ROS), sensor integration, and implementation on hardware platforms. The ideas developed will be integrated onto robotic systems and tested experimentally in the context of class projects. Not offered 20202021.
APh/EE 130
Electromagnetic Theory
9 units (306)

first term
Electromagnetic fields in vacuum: microscopic Maxwell's equations. Monochromatic fields: Rayleigh diffraction formulae, Huyghens principle, RayleighSommerfeld formula. The FresnelFraunhofer approximation. Electromagnetic field in the presence of matter, spatial averages, macroscopic Maxwell equations. Helmholtz's equation. Groupvelocity and groupvelocity dispersion. Confined propagation, optical resonators, optical waveguides. Single mode and multimode waveguides. Nonlinear optics. Nonlinear propagation. Second harmonic generation. Parametric amplification. Not offered 202021.
EE/APh 131
Light Interaction with Atomic SystemsLasers
9 units (306)

second term
Prerequisites: APh/EE 130.
Lightmatter interaction, spontaneous and induced transitions in atoms and semiconductors. Absorption, amplification, and dispersion of light in atomic media. Principles of laser oscillation, generic types of lasers including semiconductor lasers, modelocked lasers. Frequency combs in lasers. The spectral properties and coherence of laser light. Not offered 202021.
Instructor:
Yariv
APh/EE 132
Special Topics in Photonics and Optoelectronics
9 units (306)

third term
Interaction of light and matter, spontaneous and stimulated emission, laser rate equations, modelocking, Qswitching, semiconductor lasers. Optical detectors and amplifiers; noise characterization of optoelectronic devices. Propagation of light in crystals, electrooptic effects and their use in modulation of light; introduction to nonlinear optics. Optical properties of nanostructures. Not offered 202021.
ME/CS/EE 133 abc
Robotics
9 units (333)

first, second, third terms
Prerequisites: ME/CS/EE 129, may be taken concurrently, or with permission of instructor.
The course develops the core concepts of robotics. The first quarter focuses on classical robotic manipulation, including topics in rigid body kinematics and dynamics. It develops planar and 3D kinematic formulations and algorithms for forward and inverse computations, Jacobians, and manipulability. The second quarter transitions to planning, navigation, and perception. Topics include configuration space, samplebased planners, A* and D* algorithms, to achieve collisionfree motions. The third quarter discusses advanced material, for example grasping and dexterous manipulation using multifingered hands, or autonomous behaviors, or humanrobot interactions. The lectures will review appropriate analytical techniques and may survey the current research literature. Course work will focus on an independent research project chosen by the student.
Instructor:
Niemeyer
ME/CS/EE 134
Robotic Systems
9 units (360)

second term
Prerequisites: ME/CS/EE 129, may be taken concurrently, or with permission of instructor.
This course builds up, and brings to practice, the elements of robotic systems at the intersection of hardware, kinematics and control, computer vision, and autonomous behaviors. It presents selected topics from these domains, focusing on their integration into a full sensethinkact robot. The lectures will drive teambased projects, progressing from building custom robots to writing software and implementing all necessary aspects. Working systems will autonomously operate and complete their tasks during final demonstrations.
Instructor:
Niemeyer
EE/CS/EST 135
Power System Analysis
9 units (333)

first term
Prerequisites: EE 44, Ma 2, or equivalent.
Basic power system analysis: phasor representation, 3phase transmission system, transmission line models, transformer models, perunit analysis, network matrix, power flow equations, power flow algorithms, optimal powerflow (OPF) problems, swing dynamics and stability. Current research topics such as (may vary each year): convex relaxation of OPF, frequency regulation, energy functions and contraction regions, volt/var control, storage optimization, electric vehicles charging, demand response.
Instructor:
Low
EE/Ma/CS/IDS 136
Topics in Information Theory
9 units (306)

third term
Prerequisites: Ma 3 or ACM/EE/IDS 116 or CMS 117 or Ma/ACM/IDS 140a.
This class introduces information measures such as entropy, information divergence, mutual information, information density from a probabilistic point of view, and discusses the relations of those quantities to problems in data compression and transmission, statistical inference, language modeling, game theory and control. Topics include information projection, data processing inequalities, sufficient statistics, hypothesis testing, singleshot approach in information theory, large deviations.
Instructor:
Kostina
CS/EE/IDS 143
Communication Networks
9 units (333)

first term
Prerequisites: Ma 2, Ma 3, CS 24 and CS 38, or instructor permission.
This course focuses on the link layer (two) through the transport layer (four) of Internet protocols. It has two distinct components, analytical and systems. In the analytical part, after a quick summary of basic mechanisms on the Internet, we will focus on congestion control and explain: (1) How to model congestion control algorithms? (2) Is the model well defined? (3) How to characterize the equilibrium points of the model? (4) How to prove the stability of the equilibrium points? We will study basic results in ordinary differential equations, convex optimization, Lyapunov stability theorems, passivity theorems, gradient descent, contraction mapping, and Nyquist stability theory. We will apply these results to prove equilibrium and stability properties of the congestion control models and explore their practical implications. In the systems part, the students will build a software simulator of Internet routing and congestion control algorithms. The goal is not only to expose students to basic analytical tools that are applicable beyond congestion control, but also to demonstrate in depth the entire process of understanding a physical system, building mathematical models of the system, analyzing the models, exploring the practical implications of the analysis, and using the insights to improve the design.
Instructors:
Low, Ralph
CMS/CS/EE/IDS 144
Networks: Structure & Economics
12 units (345)

second term
Prerequisites: Ma 2, Ma 3, Ma/CS 6 a, and CS 38, or instructor permission.
Social networks, the web, and the internet are essential parts of our lives, and we depend on them every day. This course studies how they work and the "big" ideas behind our networked lives. Questions explored include: What do networks actually look like (and why do they all look the same)?; How do search engines work?; Why do memes spread the way they do?; How does web advertising work? For all these questions and more, the course will provide a mixture of both mathematical analysis and handson labs. The course expects students to be comfortable with graph theory, probability, and basic programming.
Instructor:
Wierman
CS/EE 145
Projects in Networking
9 units (009)

third term
Prerequisites: Either CMS/CS/EE/IDS 144 or CS/IDS 142 in the preceding term, or instructor permission.
Students are expected to execute a substantial project in networking, write up a report describing their work, and make a presentation.
Instructor:
Wierman
CS/EE 146
Control and Optimization of Networks
9 units (333)

first term
Prerequisites: Ma 2, Ma 3 or instructor's permission.
This is a researchoriented course meant for undergraduates and beginning graduate students who want to learn about current research topics in networks such as the Internet, power networks, social networks, etc. The topics covered in the course will vary, but will be pulled from current research in the design, analysis, control, and optimization of networks. Usually offered in odd years. Not offered 202021.
EE/CS 147
Digital Ventures Design
9 units (333)

first term
Prerequisites: none.
This course aims to offer the scientific foundations of analysis, design, development, and launching of innovative digital products and study elements of their success and failure. The course provides students with an opportunity to experience combined teambased design, engineering, and entrepreneurship. The lectures present a disciplined stepbystep approach to develop new ventures based on technological innovation in this space, and with invited speakers, cover topics such as market analysis, user/product interaction and design, core competency and competitive position, customer acquisition, business model design, unit economics and viability, and product planning. Throughout the term students will work within an interdisciplinary team of their peers to conceive an innovative digital product concept and produce a business plan and a working prototype. The course project culminates in a public presentation and a final report. Every year the course and projects focus on a particular emerging technology theme. Not offered 202021.
Instructor:
Staff
EE/CNS/CS 148
Selected Topics in Computational Vision
9 units (306)

third term
Prerequisites: undergraduate calculus, linear algebra, geometry, statistics, computer programming.
The class will focus on an advanced topic in computational vision: recognition, visionbased navigation, 3D reconstruction. The class will include a tutorial introduction to the topic, an exploration of relevant recent literature, and a project involving the design, implementation, and testing of a vision system.
Instructor:
Perona
EE/APh 149
Frontiers of Nonlinear Photonics
9 units (306)

second term
This course overviews recent advances in photonics with emphasis on devices and systems that utilize nonlinearities. A wide range of nonlinearities in the classical and quantum regimes is covered, including but not limited to second and thirdorder nonlinear susceptibilities, Kerr, Raman, optomechanical, thermal, and multiphoton nonlinearities. A wide range of photonic platforms is also considered ranging from bulk to ultrafast and integrated photonics. The course includes an overview of the concepts as well as review and discussion of recent literature and advances in the field. Not Offered 202021.
Instructor:
Marandi
EE 150
Topics in Electrical Engineering
Units to be arranged

terms to be arranged
Content will vary from year to year, at a level suitable for advanced undergraduate or beginning graduate students. Topics will be chosen according to the interests of students and staff. Visiting faculty may present all or portions of this course from time to time.
Instructor:
Staff
EE 151
Electromagnetic Engineering
9 units (306)

third term
Prerequisites: EE 45.
Foundations of circuit theoryelectric fields, magnetic fields, transmission lines, and Maxwell's equations, with engineering applications.
Instructor:
Yang
EE 152
High Frequency Systems Laboratory
12 units (237)

second term
Prerequisites: EE 45 or equivalent. EE 153 recommended.
The student will develop a strong, working knowledge of highfrequency systems covering RF and microwave frequencies. The essential building blocks of these systems will be studied along with the fundamental system concepts employed in their use. The first part of the course will focus on the design and measurement of core system building blocks; such as filters, amplifiers, mixers, and oscillators. Lectures will introduce key concepts followed by weekly laboratory sessions where the student will design and characterize these various system components. During the second part of the course, the student will develop their own highfrequency system, focused on a topic within remote sensing, communications, radar, or one within their own field of research.
Instructor:
Russell
EE 153
Microwave Circuits and Antennas
12 units (327)

third term
Prerequisites: EE 45.
Highspeed circuits for wireless communications, radar, and broadcasting. Design, fabrication, and measurements of microstrip filters, directional couplers, lownoise amplifiers, oscillators, detectors, and mixers. Design, fabrication, and measurements of wire antennas and arrays.
Instructor:
Antsos
EE 154 ab
Practical Electronics for Space Applications
9 units (234)

second and third terms
Part a: Subsystem Design: Students will be exposed to design for subsystem electronics in the space environment, including an understanding of the space environment, common approaches for low cost spacecraft, atmospheric / analogue testing, and discussions of risk. Emphasis on a practical exposure to early subsystem design for a TRL 34 effort. Part b: Subsystems to System Interfacing: Builds upon the first term by extending subsystems to be compatible with "spacecraft", including a nearspace "flight" of prototype subsystems on a highaltitude balloon flight. Focus on qualification for the flight environment appropriate to a TRL 45 effort. Offered 202021.
Instructor:
Klesh
CMS/CS/CNS/EE/IDS 155
Machine Learning & Data Mining
12 units (336)

second term
Prerequisites: CS/CNS/EE 156 a.
Having a sufficient background in algorithms, linear algebra, calculus, probability, and statistics, is highly recommended. This course will cover popular methods in machine learning and data mining, with an emphasis on developing a working understanding of how to apply these methods in practice. The course will focus on basic foundational concepts underpinning and motivating modern machine learning and data mining approaches. We will also discuss recent research developments.
Instructor:
Pachter
CS/CNS/EE 156 ab
Learning Systems
9 units (315)

first, third terms
Prerequisites: Ma 2 and CS 2, or equivalent.
Introduction to the theory, algorithms, and applications of automated learning. How much information is needed to learn a task, how much computation is involved, and how it can be accomplished. Special emphasis will be given to unifying the different approaches to the subject coming from statistics, function approximation, optimization, pattern recognition, and neural networks.
Instructor:
AbuMostafa
EE/Ae 157 ab
Introduction to the Physics of Remote Sensing
9 units (306)

first, second terms
Prerequisites: Ph 2 or equivalent.
An overview of the physics behind space remote sensing instruments. Topics include the interaction of electromagnetic waves with natural surfaces, including scattering of microwaves, microwave and thermal emission from atmospheres and surfaces, and spectral reflection from natural surfaces and atmospheres in the nearinfrared and visible regions of the spectrum. The class also discusses the design of modern space sensors and associated technology, including sensor design, new observation techniques, ongoing developments, and data interpretation. Examples of applications and instrumentation in geology, planetology, oceanography, astronomy, and atmospheric research.
Instructor:
van Zyl
Ge/EE/ESE 157 c
Remote Sensing for Environmental and Geological Applications
9 units (333)

third term
Analysis of electromagnetic radiation at visible, infrared, and radio wavelengths for interpretation of the physical and chemical characteristics of the surfaces of Earth and other planets. Topics: interaction of light with materials, spectroscopy of minerals and vegetation, atmospheric removal, image analysis, classification, and multitemporal studies. This course does not require but is complementary to EE 157ab with emphasis on applications for geological and environmental problems, using data acquired from airborne and orbiting remote sensing platforms. Students will work with digital remote sensing datasets in the laboratory and there will be one field trip.
Instructor:
Ehlmann
EE/APh 158
Quantum Electrical Circuits
9 units (306)

third term
Prerequisites: advancedlevel familiarity with Maxwell's electromagnetic theory and quantum mechanics (EE 151 and Ph 125 abc, or equivalent).
Course focuses on superconducting electrical systems for quantum computing. Contents begin with reviewing required concepts in microwave engineering, quantum optics, and superconductivity, and proceeds with deriving quantum mechanical description of superconducting linear circuits, Josephson qubits, and parametric amplifiers. The second part of the course provides an overview of integrated nanomechanical, piezoelectric and electrooptical systems and their applications in transducing quantum electrical signals in conjunction with superconducting qubits.
Instructor:
Mirhosseini
CS/CNS/EE/IDS 159
Advanced Topics in Machine Learning
9 units (306)

third term
Prerequisites: CS 155; strong background in statistics, probability theory, algorithms, and linear algebra; background in optimization is a plus as well.
This course focuses on current topics in machine learning research. This is a paper reading course, and students are expected to understand material directly from research articles. Students are also expected to present in class, and to do a final project. Not offered 202021.
EE/CS/IDS 160
Fundamentals of Information Transmission and Storage
9 units (306)

second term
Basics of information theory: entropy, mutual information, source and channel coding theorems. Basics of coding theory: errorcorrecting codes for information transmission and storage, block codes, algebraic codes, sparse graph codes. Basics of digital communications: sampling, quantization, digital modulation, matched filters, equalization.
Instructor:
Kostina
EE/CS 161
Big Data Networks
9 units (306)

third term
Prerequisites: Linear Algebra ACM/IDS 104 and Introduction to Probability Models ACM/EE/IDS 116 or their equivalents.
Next generation networks will have tens of billions of nodes forming cyberphysical systems and the Internet of Things. A number of fundamental scientific and technological challenges must be overcome to deliver on this vision. This course will focus on (1) How to boost efficiency and reliability in large networks; the role of network coding, distributed storage, and distributed caching; (2) How to manage wireless access on a massive scale; modern random access and topology formation techniques; and (3) New vistas in big data networks, including distributed computing over networks and crowdsourcing. A selected subset of these problems, their mathematical underpinnings, stateoftheart solutions, and challenges ahead will be covered. Given in alternate years. Not offered 202021.
Instructor:
Hassibi
EE 163
Communication Theory
9 units (306)

second term
Prerequisites: EE 111; ACM/EE/IDS 116 or equivalent.
Mathematical models of communication processes; signals and noise as random processes; sampling; modulation; spectral occupancy; intersymbol interference; synchronization; optimum demodulation and detection; signaltonoise ratio and error probability in digital baseband and carrier communication systems; linear and adaptive equalization; maximum likelihood sequence estimation; multipath channels; parameter estimation; hypothesis testing; optical communication systems. Capacity measures; multiple antenna and multiple carrier communication systems; wireless networks; different generations of wireless systems. Not Offered 202021.
Instructor:
Staff
EE 164
Stochastic and Adaptive Signal Processing
9 units (306)

third term
Prerequisites: ACM/EE/IDS 116 or equivalent.
Fundamentals of linear estimation theory are studied, with applications to stochastic and adaptive signal processing. Topics include deterministic and stochastic leastsquares estimation, the innovations process, Wiener filtering and spectral factorization, statespace structure and Kalman filters, array and fast array algorithms, displacement structure and fast algorithms, robust estimation theory and LMS and RLS adaptive fields. Given in alternate years; Offered 202021.
Instructor:
Hassibi
CS/CNS/EE/IDS 165
Foundations of Machine Learning and Statistical Inference
12 units (336)

second term
Prerequisites: CMS/ACM/IDS 113, ACM/EE/IDS 116, CS 156 a, ACM/CS/IDS 157 or instructor's permission.
The course assumes students are comfortable with analysis, probability, statistics, and basic programming. This course will cover core concepts in machine learning and statistical inference. The ML concepts covered are spectral methods (matrices and tensors), nonconvex optimization, probabilistic models, neural networks, representation theory, and generalization. In statistical inference, the topics covered are detection and estimation, sufficient statistics, CramerRao bounds, RaoBlackwell theory, variational inference, and multiple testing. In addition to covering the core concepts, the course encourages students to ask critical questions such as: How relevant is theory in the age of deep learning? What are the outstanding open problems? Assignments will include exploring failure modes of popular algorithms, in addition to traditional problemsolving type questions.
Instructor:
Anandkumar
CMS/CS/EE 166
Computational Cameras
12 units (336)

third term
Prerequisites: ACM 104 or ACM 107 or equivalent.
Computational cameras overcome the limitations of traditional cameras, by moving part of the image formation process from hardware to software. In this course, we will study this emerging multidisciplinary field at the intersection of signal processing, applied optics, computer graphics, and vision. At the start of the course, we will study modern image processing and image editing pipelines, including those encountered on DSLR cameras and mobile phones. Then we will study the physical and computational aspects of tasks such as coded photography, lightfield imaging, astronomical imaging, medical imaging, and timeofflight cameras. The course has a strong handson component, in the form of homework assignments and a final project. In the homework assignments, students will have the opportunity to implement many of the techniques covered in the class. Example homework assignments include building an endtoend HDR imaging pipeline, implementing Poisson image editing, refocusing a lightfield image, and making your own lensless "scotchtape" camera.
Instructor:
Bouman
EE/CS/IDS 167
Introduction to Data Compression and Storage
9 units (306)

third term
Prerequisites: Ma 3 or ACM/EE/IDS 116.
The course will introduce the students to the basic principles and techniques of codes for data compression and storage. The students will master the basic algorithms used for lossless and lossy compression of digital and analog data and the major ideas behind coding for flash memories. Topics include the Huffman code, the arithmetic code, LempelZiv dictionary techniques, scalar and vector quantizers, transform coding; codes for constrained storage systems. Given in alternate years; Not offered 202021.
Instructor:
Kostina
MedE/EE/BE 168 abc
Biomedical Optics: Principles and Imaging
9 units (405)

parts a and b are taught in second and third terms in odd academic years, and part c is taught in second term in even academic years
Prerequisites: instructor's permission.
Part a covers the principles of optical photon transport in biological tissue. Topics include a brief introduction to biomedical optics, singlescatterer theories, Monte Carlo modeling of photon transport, convolution for broadbeam responses, radiative transfer equation and diffusion theory, hybrid Monte Carlo method and diffusion theory, and sensing of optical properties and spectroscopy, (absorption, elastic scattering, Raman scattering, and fluorescence). Part b covers established optical imaging technologies. Topics include ballistic imaging (confocal microscopy, twophoton microscopy, superresolution microscopy, etc.), optical coherence tomography, Mueller optical coherence tomography, and diffuse optical tomography. Part c covers emerging optical imaging technologies. Topics include photoacoustic tomography, ultrasoundmodulated optical tomography, optical time reversal (wavefront shaping/engineering), and ultrafast imaging. MedE/EE/BE 168 ab not offered 20202021. MedE/EE/BE 168 c offered 20202021.
Instructor:
Wang
ACM/EE/IDS 170
Mathematics of Signal Processing
12 units (309)

third term
Prerequisites: ACM/IDS 104, CMS/ACM/IDS 113, and ACM/EE/IDS 116; or instructor's permission.
This course covers classical and modern approaches to problems in signal processing. Problems may include denoising, deconvolution, spectral estimation, directionofarrival estimation, array processing, independent component analysis, system identification, filter design, and transform coding. Methods rely heavily on linear algebra, convex optimization, and stochastic modeling. In particular, the class will cover techniques based on leastsquares and on sparse modeling. Throughout the course, a computational viewpoint will be emphasized.
Instructor:
Hassibi
EE/CS/MedE 175
Digital Circuits Analysis and Design with Complete VHDL and RTL Approach
9 units (360)

third term
Prerequisites: medium to advanced knowledge of digital electronics.
A careful balance between synthesis and analysis in the development of digital circuits plus a truly complete coverage of the VHDL language. The RTL (register transfer level) approach. Study of FPGA devices and comparison to ASIC alternatives. Tutorials of software and hardware tools employed in the course. VHDL infrastructure, including lexical elements, data types, operators, attributes, and complex data structures. Detailed review of combinational circuits followed by full VHDL coverage for combinational circuits plus recommended design practices. Detailed review of sequential circuits followed by full VHDL coverage for sequential circuits plus recommended design practices. Detailed review of state machines followed by full VHDL coverage and recommended design practices. Construction of VHDL libraries. Hierarchical design and practice on the hard task of project splitting. Automated simulation using VHDL testbenches. Designs are implemented in stateoftheart FPGA boards. Not Offered 202021.
Instructor:
Pedroni
EE/APh 180
Nanotechnology
6 units (303)

first term
This course will explore the techniques and applications of nanofabrication and miniaturization of devices to the smallest scale. It will be focused on the understanding of the technology of miniaturization, its history and present trends towards building devices and structures on the nanometer scale. Examples of applications of nanotechnology in the electronics, communications, data storage and sensing world will be described, and the underlying physics as well as limitations of the present technology will be discussed.
Instructor:
Scherer
APh/EE 183
Physics of Semiconductors and Semiconductor Devices
9 units (306)

third term
Principles of semiconductor electronic structure, carrier transport properties, and optoelectronic properties relevant to semiconductor device physics. Fundamental performance aspects of basic and advanced semiconductor electronic and optoelectronic devices. Topics include energy band theory, carrier generation and recombination mechanisms, quasiFermi levels, carrier drift and diffusion transport, quantum transport.
Instructor:
NadjPerge
EE/BE/MedE 185
MEMS Technology and Devices
9 units (306)

third term
Prerequisites: APh/EE 9 ab, or instructor's permission.
Microelectromechanical systems (MEMS) have been broadly used for biochemical, medical, RF, and labonachip applications. This course will cover both MEMS technologies (e.g., micro and nanofabrication) and devices. For example, MEMS technologies include anisotropic wet etching, RIE, deep RIE, micro/nano molding and advanced packaging. This course will also cover various MEMS devices used in microsensors and actuators. Examples will include pressure sensors, accelerometers, gyros, FR filters, digital mirrors, microfluidics, micro totalanalysis system, biomedical implants, etc. Not offered 202021.
CNS/Bi/EE/CS/NB 186
Vision: From Computational Theory to Neuronal Mechanisms
12 units (444)

second term
Lecture, laboratory, and project course aimed at understanding visual information processing, in both machines and the mammalian visual system. The course will emphasize an interdisciplinary approach aimed at understanding vision at several levels: computational theory, algorithms, psychophysics, and hardware (i.e., neuroanatomy and neurophysiology of the mammalian visual system). The course will focus on early vision processes, in particular motion analysis, binocular stereo, brightness, color and texture analysis, visual attention and boundary detection. Students will be required to hand in approximately three homework assignments as well as complete one project integrating aspects of mathematical analysis, modeling, physiology, psychophysics, and engineering. Given in alternate years; Not Offered 202021.
Instructors:
Meister, Perona, Shimojo, Tsao
EE/MedE 187
VLSI and ULSI Technology
9 units (306)

third term
Prerequisites: APh/EE 9 ab, EE/APh 180 or instructor's permission.
This course is designed to cover the stateoftheart micro/nanotechnologies for the fabrication of ULSI including BJT, CMOS, and BiCMOS. Technologies include lithography, diffusion, ion implantation, oxidation, plasma deposition and etching, etc. Topics also include the use of chemistry, thermal dynamics, mechanics, and physics. Not offered 202021.
BE/EE/MedE 189 ab
Design and Construction of Biodevices
189 a, 12 units (363) offered both first and third terms; 189 b, 9 units (090) offered only third term
Prerequisites: BE/EE/MedE 189 a must be taken before BE/EE/MedE 189 b.
Part a, students will design and implement computercontrolled biosensing systems, including a pulse monitor, a pulse oximeter, and a realtime polymerasechainreaction incubator. Part b is a studentinitiated design project requiring instructor's permission for enrollment. Enrollment is limited to 24 students.
Instructors:
Bois, Yang
MedE/EE 268
Medical Imaging
9 units (405)

third term
Medical imaging technologies will be covered. Topics include Xray radiography, Xray computed tomography (CT), nuclear imaging (PET & SPECT), ultrasonic imaging, and magnetic resonance imaging (MRI).
Instructor:
Lihong Wang
EE 291
Advanced Work in Electrical Engineering
Units to be arranged
Special problems relating to electrical engineering. Primarily for graduate students; students should consult with their advisers.
Published Date:
July 28, 2022