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2010-11 Catalog: Electrical Engineering

EE 1

Introduction to Electrical Engineering Seminar

1 unit   |  second term
Required for EE undergraduates. Weekly seminar given by faculty in the department broadly describing different areas of electrical engineering: circuits and VLSI, communications, control, devices, images and vision, information theory, learning and pattern recognition, MEMS and micromachining, networks, electromagnetics and opto-electronics, RF and microwave circuits and antennas, robotics and signal processing, and specifically, research going on at Caltech.
Instructor: Staff
EE 5

Introduction to Embedded Systems

6 units (2-3-1)   |  third term
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. Topics include basic digital logic, CPU and embedded system architecture, and embedded systems programming principles (events, user interfaces, and multitasking). The class is intended for students who wish to gain a basic understanding of embedded systems or for those who would like an introduction to the material before taking EE/CS 51/52. Graded pass/fail.
Instructor: George
APh/EE 9 ab

Solid-State Electronics for Integrated Circuits

6 units (2-2-2)   |  first, second terms
Prerequisites: Successful completion of APh/EE 9 a is a prerequisite for enrollment in APh/EE 9 b.
Introduction to solid-state 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 computer-aided layout, and fabrication and testing of light-emitting diodes, transistors, and inverters. Students learn photolithography, and use of vacuum systems, furnaces, and device-testing equipment.
Instructor: Scherer
EE 40

Introduction to Semiconductors and Sensors

9 units (3-0-6)   |  third term
Prerequisites: APh/EE 9 ab, Ma 2, Ph 2.
This course provides an introduction to semiconductors and semiconductor sensors. The fundamental physics of semiconductor electronics and devices will be emphasized, together with their applications. Devices that will be discussed include photoconductors, diodes, transistors, CCDs, MOS/MOSFET/MOS imagers, temperature sensors, magnetic sensors, thermoelectricity, piezoresistivity, piezoelectrics, etc.
Instructor: Tai
EE 45

Electronics Laboratory

12 units (3-3-6)   |  third term
Prerequisites: should be taken concurrently with EE 40, or with instructor's permission; Ma 2 a, Ph 1abc.
Fundamentals of electronics and circuit analysis. Lectures and laboratory sessions on linear circuits, transient response, steady-state sinusoidal response and phasors, transformers, diodes, transistors, small-signal analysis, gain stages, operational amplifiers; an introduction to electrical and analog electronic systems such as radio and audio systems.
Instructor: Emami
EE/CS 51

Principles of Microprocessor Systems

12 units (4-5-3)   |  first term
The principles and design of microprocessor-based computer systems. Lectures cover both hardware and software aspects of microprocessor system design such as interfacing to input and output devices, user interface design, real-time systems, and table-driven software. The homework emphasis is on software development, especially interfacing with hardware, in assembly language.
Instructor: George
EE/CS 52

Microprocessor Systems Laboratory

12 units (1-11-0)   |  second term
Prerequisites: EE/CS 51 or equivalent.
The student will design, build, and program a specified microprocessor-based system. This structured laboratory is organized to familiarize the student with electronic circuit construction techniques, modern development facilities, and standard design techniques. The lectures cover topics in microprocessor system design such as display technologies, interfacing with analog systems, and programming microprocessors in high-level languages.
Instructor: George
EE/CS 53 abc

Microprocessor Project Laboratory

12 units (0-12-0)   |  first, second, third terms
Prerequisites: EE/CS 52 or equivalent.
A project laboratory to permit the student to select, design, and build a microprocessor-based system. The student is expected to take a project from proposal through design and implementation (possibly including PCB fabrication) to final review and documentation.
Instructor: George
CS/EE/ME 75 abc

Introduction to Multidisciplinary Systems Engineering

3 units (2-0-1) , 6 units (2-0-4), or 9 units (2-0-7) first term; 6 units (2-3-1), 9 units (2-6-1), or 12 units (2-9-1) second term; 12 units (2-9-1), 15 units (2-12-1), or 18 units (2-15-1), with instructor's permission, third term   |  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.
Instructors: Murray, Atwater, Hunt
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: Potter
EE 90

Analog Electronics Project Laboratory

9 units (1-8-0)   |  second, third terms
Prerequisites: EE 40 and EE 45.
A structured laboratory course that gives the student the opportunity to design and build a sequence of simple analog electronics projects. The goal is to gain familiarity with circuit design and construction, component selection, CAD support, and debugging techniques.
Instructor: Megdal
EE 91 ab

Experimental Projects in Electronic Circuits

Units by arrangement; 12 units minimum each term   |  first, second terms
Prerequisites: EE 45. Recommended: EE/CS 51 and 52, and EE 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. Text: literature references.
Instructor: Megdal
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: Hassibi
EST/EE/ME 109 ab

Energy

9 units (3-0-6)   |  first, second terms
Prerequisites: Ph 1 abc and Ma 2 ab.
Modeling and forecasting. Heating, transportation, and electricity demand. Historical energy sources: wood and whale oil. Fossil-fuel supplies: oil, natural gas, coal, oil sands, and oil shale. Alternative energy sources: hydroelectric, nuclear, wind, biomass, geothermal, biofuels, waves, ocean thermal, solar photovoltaic, and solar thermal. Thermodynamics of energy conversion: vapor power cycles, combustion, combined cycle, and fuel cells. Transportation systems: internal combustion engines, gas turbines, and electric vehicles. Energy systems: pipelines, rail and water transport, shipping, carbon capture and sequestration, transmission lines and electricity distribution networks. Energy policy: efficiency regulations, biofuels vs food, water impacts, air pollution, and climate.
Instructors: Rutledge, Shepherd
EE 111

Signals, Systems, and Transforms

9 units (3-0-6)   |  first term
Prerequisites: Ma 1, Ma 2. EE 45 recommended.
An introduction to continuous and discrete time signals and systems. Study of the Fourier transform, Fourier series, the Laplace transform, Z-transforms, and the fast Fourier transform as applied in electrical engineering. Various types of systems, with emphasis on linear and time invariant systems. Transfer functions, difference and differential equations, state space representations, system realizations with block diagrams, and analysis of transient and steady state responses. Sampling theorems for analog to digital conversion.
Instructor: Vaidyanathan
EE 112

Introduction to Digital Signal Processing

9 units (3-0-6)   |  second term
Prerequisites: EE 111 or equivalent.
Fundamentals of digital signal processing, digital representations, analog to digital conversions, fast Fourier transformation, digital filtering, filter structures, quantization and stability analysis, roundoff noise calculations, and applications in various areas. Given in alternate years; offered 2010-11.
Instructor: Vaidyanathan
EE 113

Feedback and Control Circuits

12 units (4-4-4)   |  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 (Proportional-Integrated-Derivative) control, digital control, and fuzzy control. There is a significant laboratory component to this course, in which the student will be expected to build, analyze, test, and measure the circuits and systems discussed in the lectures.
Instructor: George
EE 114 ab

Analog Circuit Design

12 units (4-0-8)   |  first, second terms
Prerequisites: EE 45 or equivalent, EE 114 a or equivalent.
Analysis and design of analog circuits at the transistor level. Emphasis on intuitive design methods, quantitative performance measures, and practical circuit limitations. Circuit performance evaluated by hand calculations and computer simulations. Recommended for seniors and graduate students. First term deals with continuous time and amplitude signals; physics of bipolar and MOS transistors, low-frequency behavior of single-stage and multistage amplifiers, current sources, active loads, differential amplifiers, operational amplifiers, and supply and temperature independent biasing. Second term covers high-frequency response of amplifiers, feedback in electronic circuits, stability of feedback amplifiers, and noise in electronic circuits. A number of the following topics will be covered each year: translinear circuits, switched capacitor circuits, data conversion circuits (A/D and D/A), continuous-time Gm.C filters and phase locked loops.
Instructor: Hajimiri
ACM/EE 116

Introduction to Stochastic Processes and Modeling

9 units (3-0-6)   |  first term
Prerequisites: Ma 2 ab or instructor's permission.
Introduction to fundamental ideas and techniques of stochastic analysis and modeling. Random variables, expectation and conditional expectation, joint distributions, covariance, moment generating function, central limit theorem, weak and strong laws of large numbers, discrete time stochastic processes, stationarity, power spectral densities and the Wiener-Khinchine theorem, Gaussian processes, Poisson processes, Brownian motion. The course develops applications in selected areas such as signal processing (Wiener filter), information theory, genetics, queuing and waiting line theory, and finance.
Instructor: Tropp
Ph/EE 118

Low-Noise Electronic Measurement

9 units (3-0-6)   |  second term
Prerequisites: Ph 105 or equivalent.
An introduction to ultralow-noise electrical measurements and sensor technology as applied to experimental research. Topics include physical noise processes, signal transduction, synchronous and lock-in detection, digital signal transforms, and other aspects of precision measurements. Specific sensor technologies will include SQUID sensors, single electron transistors, transition-edge sensors, tunnel junction detectors, micro- and nanomechanical detectors, and biosensors.
Instructor: Roukes
EE 119 abc

Advanced Digital Systems Design

9 units (3-3-3)   |  first, second, third terms
Prerequisites: EE/CS 52 or CS/EE 181 a.
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, application-specific 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 self-proposed systems using a variety of technologies and tools.
EE 124

Mixed-mode Integrated Circuits

9 units (3-0-6)   |  third term
Prerequisites: EE 114 a or equivalent.
Introduction to selected topics in mixed-signal 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, high-speed 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 125

Digital Electronics and Design with FPGAs and VHDL

9 units (3-6-0)   |  second 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 combinational-logic, combinational-arithmetic, sequential, and state-machine circuits. Detailed tutorials for synthesis and simulation tools using FPGAs and VHDL. Wide selection of complete, real-world fundamental advanced projects, including theory, design, simulation, and physical implementation. All designs are implemented using state-of-the-art development boards.
Instructor: Pedroni
EE/Ma 126 ab

Information Theory

9 units (3-0-6)   |  first, second terms
Prerequisites: Ma 2.
Shannon's mathematical theory of communication, 1948-present. 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, first- order Markov, ergodic, and Gaussian. Calculation of capacity-cost and rate-distortion functions. Kolmogorov complexity and 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 127, EE 161, and/or EE 167 should prepare the student for research in information theory, coding theory, wireless communications, and/or data compression.
Instructor: Effros
EE/Ma/CS 127

Error-Correcting Codes

9 units (3-0-6)   |  third term
Prerequisites: Ma 2.
This course, a sequel to EE/Ma 126 a, may be taken independently; it will develop 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, Golay, Fire, BCH, Reed-Solomon (including a self-contained introduction to the theory of finite fields); and the modern theory of sparse graph codes with iterative decoding, e.g. LDPC codes, fountain coding. Emphasis will be placed on the associated encoding and decoding algorithms, and students will be asked to demonstrate their understanding with a software project.
Instructor: Ho
EE 128 ab

Selected Topics in Digital Signal Processing

9 units (3-0-6)   |  second, third terms
Prerequisites: EE 111 and EE 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.
CS/EE/Ma 129 abc

Information and Complexity

9 units (3-0-6), first and second terms; (1-4-4) third term   |  first, second, third terms
Prerequisites: basic knowledge of probability and discrete mathematics.
A basic course in information theory and computational complexity with emphasis on fundamental concepts and tools that equip the student for research and provide a foundation for pattern recognition and learning theory. First term: what information is and what computation is; entropy, source coding, Turing machines, uncomputability. Second term: topics in information and complexity; Kolmogorov complexity, channel coding, circuit complexity, NP-completeness. Third term: theoretical and experimental projects on current research topics.
APh/EE 130

Electromagnetic Theory

9 units (3-0-6)   |  first term
This course reviews EM theory and optical concepts that are frequently encountered. EM theory: tensor matrix, kDB space, Poynting theorem. Dispersion and absorption. Reflection at an interface. Nonlinear optics. Polarization: Jones matrix and Stokes vectors. Ray tracing: ABCD matrix, optical aberrations. Noise. Diffraction. Interferometry: system design, homodyne, heterodyne, spectral domain analysis.
Instructor: Yariv
EE/APh 131

Optical Wave Propagation

9 units (3-0-6)   |  second term
This course focuses on optical wave propagation and related applications. Topics to be covered include Huygens' principle, Fourier optics, Gaussian waves, imaging, gratings, spectroscopy, interferometry, Fabry-Perot cavities, coherence, holography, femtosecond optics, dispersion, Kramers-Kronig relation, Mie scattering theory, photonic band gaps, and near-field imaging.
Instructor: Staff
APh/EE 132

Optoelectronic Materials and Devices

9 units (3-0-6)   |  third term
Interaction of light and matter, spontaneous and stimulated emission, laser rate equations, mode-locking, Q-switching, semiconductor lasers. Optical detectors and amplifiers; noise characterization of optoelectronic devices. Propagation of light in crystals, electro-optic effects and their use in modulation of light; introduction to nonlinear optics. Optical properties of nanostructures.
Instructor: Yariv
CS/EE 143

Communication Networks

9 units (3-3-3)   |  first term
Prerequisites: Ma 2 ab.
This course introduces the basic mechanisms and protocols in communication networks, and mathematical models for their analysis. It covers topics such as digitization, switching, switch design, routing, error control (ARQ), congestion control, layering, queuing models, optimization models, basics of protocols in the Internet, wireless networks, and optical networks. This course can be combined with CS/EE 144 and CS/EE 145 to satisfy the project requirement for CS undergraduate degree.
Instructor: Low
CS/EE 144

Ideas behind the Web

9 units (3-0-6)   |  second term
Prerequisites: Ma 2 ab.
The Web is an essential part of our lives, and we all depend on it every day, but do you really know what makes it work? This course studies the "big" ideas behind the Web: How do search engines work? How can search engines make so much money from putting ads next to their search results? Are there ways to prevent spammers from accumulating lots of e-mail addresses? What does the Web actually look like? How big is the Web? For all these questions and more, the course will provide a mixture of both mathematical models and real-world, hands-on labs. This course can be combined with CS/EE 143 and CS/EE 145 to satisfy project requirement for CS undergraduate degree.
Instructor: Wierman
CS/EE 145

Projects in Networking

9 units (0-0-9)   |  third term
Prerequisites: CS/EE 143, CS/EE 144.
Students are expected to execute a substantial project in networking, write up a report describing their work, and make a presentation. This course can be combined with CS/EE 143 and CS/EE 144 to satisfy the project requirement for CS undergraduate degree.
Instructors: Low, Wierman
CS/EE 146

Advanced Networking

9 units (3-3-3)   |  third term
Prerequisites: CS/EE 143 or instructor's permission.
This is a research-oriented 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 topics in the design, analysis, control, and optimization of networks, protocols, and Internet applications. Usually offered in alternate years.
Instructor: Wierman
CS/EE 147

Network Performance Analysis

9 units (3-0-6)   |  third term
Prerequisites: Ma 2 ab is required. CS/EE 143, CS/EE 144, and ACM 116 are recommended.
When designing a network protocol, distributed system, etc., it is essential to be able to quantify the performance impacts of design choices along the way. For example, should we invest in more buffer space or a faster processor? One fast disk or multiple slower disks? How should requests be scheduled? What dispatching policy will work best? Ideally, one would like to make these choices before investing the time and money to build a system. This class will teach students how to answer this type of "what if" question by introducing students to analytic performance modeling, the tools necessary for rigorous system design. The course will focus on the mathematical tools of performance analysis (which include stochastic modeling, scheduling theory, and queueing theory) but will also highlight applications of these tools to real systems. Usually offered in alternate years.
EE/CNS/CS 148 ab

Selected Topics in Computational Vision

9 units (3-0-6)   |  first, third terms
Prerequisites: undergraduate calculus, linear algebra, geometry, statistics, computer programming.
The class will focus on an advanced topic in computational vision: recognition, vision-based navigation, 3-D 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 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 (3-0-6)   |  second term
Prerequisites: EE 45.
Foundations of circuit theory-electric fields, magnetic fields, transmission lines, and Maxwell's equations, with engineering applications.
Instructor: Rutledge
EE 153

Microwave Circuits and Antennas

12 units (3-2-7)   |  third term
Prerequisites: EE 45.
High-speed circuits for wireless communications, radar, and broadcasting. Design, fabrication, and measurements of microstrip filters, directional couplers, low-noise amplifiers, oscillators, detectors, and mixers. Design, fabrication, and measurements of wire antennas and arrays.
Instructor: Antsos
CS/CNS/EE 154

Artificial Intelligence

9 units (3-3-3)   |  first term
Prerequisites: Ma 2 b or equivalent, and CS 1 or equivalent.
How can we build systems that perform well in unk nown environments and unforeseen situations? How can we develop systems that exhibit "intelligent" behavior, without prescribing explicit rules? How can we build systems that learn from experience in order to improve their performance? We will study core modeling techniques and algorithms from statistics, optimization, planning, and control and study applications in areas such as sensor networks, robotics, and the Internet. The course is designed for upper-level undergraduate and graduate students.
Instructor: Krause
CS/CNS/EE 155

Probabilistic Graphical Models

9 units (3-3-3)   |  second term
Prerequisites: background in algorithms and statistics (CS/CNS/EE 154 or CS/CNS/EE 156 a or instructor's permission).
Many real-world problems in AI, computer vision, robotics, computer systems, computational neuroscience, computational biology, and natural language processing require one to reason about highly uncertain, structured data, and draw global insight from local observations. Probabilistic graphical models allow addressing these challenges in a unified framework. These models generalize approaches such as hidden Markov models and Kalman filters, factor analysis, and Markov random fields. In this course, we will study the problem of learning such models from data, performing inference (both exact and approximate), and using these models for making decisions. The techniques draw from statistics, algorithms, and discrete and convex optimization. The course will be heavily research- oriented, covering current developments such as probabilistic relational models, models for naturally combining logical and probabilistic inference, and nonparametric Bayesian methods.
Instructor: Krause
CS/CNS/EE 156 ab

Learning Systems

9 units (3-0-6)   |  first, second 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.
EE/Ae 157 ab

Introduction to the Physics of Remote Sensing

9 units (3-0-6)   |  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 near-infrared 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
CS/CNS/EE 159

Projects in Machine Learning and AI

9 units (0-0-9)   |  third term
Prerequisites: CS/CNS/EE 154 or CS/CNS/EE 156 b.
Students are expected to execute a substantial project in AI and/or machine learning, write up a report describing their work, and make a presentation. This course can be combined with CS/CNS/EE 154/155 or with CS/CNS/EE 156 ab to satisfy the project requirement for the CS undergraduate degree.
EE 160

Communication-System Fundamentals

9 units (3-0-6)   |  second term
Prerequisites: EE 111.
Laws of radio and guided transmission, noise as a limiting factor, AM and FM signals and signal-to-noise ratio, sampling and digital transmission, errors, information theory, error correction. Emphasis will be on fundamental laws and equations and their use in communication-system designs, including voice, video, and data.
Instructor: Hassibi
EE 161

Wireless Communications

9 units (3-0-6)   |  third term
Prerequisites: EE 160.
This course will cover the fundamentals of wireless channels and channel models, wireless communication techniques, and wireless networks. Topics include statistical models for time-varying narrowband and wideband channels, fading models for indoor and outdoor systems, macro- and microcellular system design, channel access and spectrum sharing using TDMA, FDMA, and CDMA, time-varying channel capacity and spectral efficiency, modulation and coding for wireless channels, antenna arrays, diversity combining and multiuser detection, dynamic channel allocation, and wireless network architectures and protocols.
Instructor: Hassibi
EE 163 ab

Communication Theory

9 units (3-0-6)   |  second, third terms
Prerequisites: EE 111; ACM/EE 116 or equivalent.
Least mean square error linear filtering and prediction. Mathematical models of communication processes; signals and noise as random processes; sampling and quantization; modulation and spectral occupancy; intersymbol interference and synchronization considerations; signal-to-noise ratio and error probability; optimum demodulation and detection in digital baseband and carrier communication systems.
Instructors: Ho, Quirk
EE 164

Stochastic and Adaptive Signal Processing

9 units (3-0-6)   |  third term
Prerequisites: ACM/EE 116 or equivalent.
Fundamentals of linear estimation theory are studied, with applications to stochastic and adaptive signal processing. Topics include deterministic and stochastic least-squares estimation, the innovations process, Wiener filtering and spectral factorization, state-space structure and Kalman filters, array and fast array algorithms, displacement structure and fast algorithms, robust estimation theory and LMS and RLS adaptive fields.
Instructor: Hassibi
EE/BE 166

Optical Methods for Biomedical Imaging and Diagnosis

9 units (3-1-5)   |  first term
Prerequisites: EE 151 or equivalent.
Topics include Fourier optics, scattering theories, shot noise limit, energy transitions associated with fluorescence, phosphorescence, and Raman emissions. Study of coherent anti-Stokes Raman spectroscopy (CARS), second harmonic generation and near-field excitation. Scattering, absorption, fluorescence, and other optical properties of biological tissues and the changes in these properties during cancer progression, burn injury, etc. Specific optical technologies employed for biomedical research and clinical applications: optical coherence tomography, Raman spectroscopy, photon migration, acousto-optics (and opto-acoustics) imaging, two photon fluorescence microscopy, and second- and third-harmonic microscopy.
Instructor: Yang
EE 167

Data Compression

9 units (3-0-6)   |  third term
Prerequisites: EE/Ma 126 or instructor's permission.
An introduction to the basic results, both theoretical and practical, of data compression. Review of relevant background from information theory. Fixed model and adaptive Huffman and arithmetic codes. The Lempel-Ziv algorithm and its variants. Scalar and vector quantization, including the Lloyd-Max quantizers, and the generalized Lloyd algorithm. Transform coding. Karhuenen-Loeve and discrete cosine transforms. The bit allocation problem. Subband coding. Practical algorithms for image and video compression.
EE/APh 180

Solid-State Devices

9 units (3-0-6)   |  second term
Prerequisites: EE 45.
Starting with the phenomenological statement of physical processes, the operation of a device is derived from fundamental principles and the device's materials and design. Subjects include the motion of charge carriers in solids, equilibrium statistics, the electronic structure of solids, doping, nonequilibrium states, the pn junction, the junction transistor, the Schottky diode, the field-effect transistor, the light-emitting diode, and the photodiode.
Instructor: Scherer
CS/EE 181 abc

VLSI Design Laboratory

12 units (3-6-3)   |  first, second, third terms
Digital integrated system design, with projects involving the design, verification, and testing of high-complexity CMOS microcircuits. First-term lecture and homework topics emphasize disciplined design, and include CMOS logic, layout, and timing; computer-aided design and analysis tools; and electrical and performance considerations. Each student is required in the first term to complete individually the design, layout, and verification of a moderately complex integrated circuit. Advanced topics second and third terms include self-timed design, computer architecture, and other topics that vary year by year. Projects are large-scale designs done by teams. Only (a) and (b) offered 2010-11.
Instructor: Martin
APh/EE 183

Physics of Semiconductors and Semiconductor Devices

9 units (3-0-6)   |  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, quasi-Fermi levels, carrier drift and diffusion transport, quantum transport.
Instructor: Atwater
CS/EE 184 ab

Computer Architecture

9 units (3-3-3)   |  second, third terms
Prerequisites: CS 21 and CS 24, or instructor's permission.
Organization and design of physical computational systems, basic building blocks for computations, understanding and exploiting structure in computational problems, design space, costs, and trade-offs in computer organization, common machine abstractions, and implementation/optimization techniques. The course will develop the fundamental issues and trade-offs that define computer organizational and architectural styles, including RISC, VLIW, Super Scalar, EPIC, SIMD, Vector, MIMD, reconfigurable, FPGA, PIM, and SoC. Basic topics in the design of computational units, instruction organization, memory systems, control and data flow, interconnect, and the hardware-software abstraction will also be covered.
EE/BE 185

MEMS Technology and Devices

9 units (3-0-6)   |  third term
Prerequisites: APh/EE 9 ab, or instructor's permission.
Micro-electro-mechanical systems (MEMS) have been broadly used for biochemical, medical, RF, and lab-on-a-chip 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 total-analysis system, biomedical implants, etc.
Instructor: Tai
CNS/Bi/EE 186

Vision: From Computational Theory to Neuronal Mechanisms

12 units (4-4-4)   |  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 2010-11.
Instructors: Perona, Shimojo, Koch
EE 187

VLSI and ULSI Technology

9 units (3-0-6)   |  first term
Prerequisites: APh/EE 9 ab, EE/APh 180 or instructor's permission.
This course is designed to cover the state-of-the-art 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.
CNS/CS/EE 188

Topics in Computation and Biological Systems

9 units (3-0-6)   |  second term
Prerequisites: Ma 2 or IST 4.
Advanced topics related to computational methods in biology. Topics might change from year to year. Examples include spectral analysis techniques and their applications in threshold circuits complexity and in computational learning theory. The role of feedback in computation. The logic of computation in gene regulation networks. The class includes a project that has the goal of learning how to understand, criticize, and present the ideas and results in research papers.
BE/EE 189 ab

Design and Construction of Biodevices

12 units (3-6-3) first term, 9 units (0-9-0) second term   |  first, second terms
Prerequisites: ACM 95 ab (for BE/EE 189 a); BE/EE 189 a (for BE/EE 189 b).
First term, students will design and implement biosensing systems, including a pulse monitor, a pulse oximeter, and a real-time polymerase-chain-reaction incubator. Students will learn to program in LABVIEW. Second term is a student-initiated design project requiring instructor's permission for enrollment. Enrollment is limited to 24 students. BE/EE 189 a is an option requirement; second term is not.
Instructor: C. Yang
EE 226

Advanced Information and Coding Theory

9 units (3-0-6)   |  first term
A selection of topics in information theory and coding theory not normally covered in EE/Ma 126 ab or EE/Ma/CS 127. These topics include constrained noiseless codes, constructive coding theorems for erasure channels, density evolution, repeat-accumulate and related codes, and network coding.
EE 243 abc

Quantum Electronics Seminar

6 units (3-0-3)   |  first, second, third terms
Advanced treatment of topics in the field of quantum electronics. Each weekly seminar consists of a review and discussion of results in the areas of quantum electronics and optoelectronics.
Instructor: Yariv
CS/EE 245

Special Topics in Networking

9 units (3-3-3)   |  second term
Prerequisites: CS/EE 143 and CS/EE 144 or instructor's permission.
This course is an advanced, research-oriented seminar in communication networks meant for graduate students and advanced undergraduates. The topics covered in the course will vary, but will always come from the cutting edge of networking research. Examples of possible topics are error-correcting codes, wireless networking, scheduling theory, and congestion control.
Instructor: Low
CS/CNS/EE 253

Special Topics in Machine Learning

9 units (3-3-3)
Prerequisites: CS/CNS/EE 154 or CS/CNS/EE 156 a or instructor's permission.
This course is an advanced, research-oriented seminar in machine learning and AI meant for graduate students and advanced undergraduates. The topics covered in the course will vary, but will always come from the cutting edge of machine learning and AI research. Examples of possible topics are active learning and optimized information gathering, AI in distributed systems, computational learning theory, machine learning applications (on the Web, in sensor networks and robotics).
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