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
EE/ME 7
Introduction to Mechatronics
6 units (2-3-1)
|
second term
Mechatronics is the multi-disciplinary design of electro-mechanical 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.
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 Devices
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 44
Circuits and Systems
9 units (3-0-6)
|
first term
Prerequisites: Ph1 abc, should be taken concurrently with Ma 2 a and Ph 2 a.
Fundamentals of circuits and network theory, circuit elements, linear circuits, terminals and port presentation, nodal and mesh analysis, time-domain analysis of circuits and systems, sinusoidal response, introductory frequency domain analysis, transfer functions, poles and zeros, time and transfer constants, network theorems, transformers.
Instructor:
Hajimiri
EE 45
Electronics Laboratory
12 units (3-3-6)
|
second term
Prerequisites: EE 44.
Fundamentals of electronic circuits and systems. Lectures on diodes, transistors, small-signal 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, steady-state sinusoidal response and phasors, diodes, transistors, amplifiers.
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
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. May be repeated for credit.
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
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 2013-14.
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)
|
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:
Megdal
EE 91 ab
Experimental Projects in Electronic Circuits
Units by arrangement; first, second terms
|
12 units minimum each term
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
Energy Technology and Policy
9 units (3-0-6)
|
first term
Prerequisites: Ph 1 abc, Ch 1 ab and Ma 1 abc.
Fossil fuels, alternatives, electricity, agriculture, and transportation. Combustion, internal combustion engines, gas and steam turbines. Fracking, mining, pollution, resources, efficiency, renewables, climate.
Instructors:
Rutledge, Shepherd
EE 111
Signal-Processing Systems and Transforms
9 units (3-0-6)
|
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, z-transforms, and the fast Fourier transform as applied in electrical engineering. Sampling theorems for continuous to discrete-time 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 Digital Signal Processing
9 units (3-0-6)
|
second term
Prerequisites: EE 111 or equivalent. Math 3 recommended.
Fundamentals of digital signal processing, digital filtering, recursive and non recursive filters, linear phase and minimum phase systems, digital filter structures, allpass filters and applications, quantization and stability analysis, round-off noise calculations, Nyquist and sub-Nyquist sampling, elements of multrirate signal processing, reconstruction of sparsely sampled signals, statistical signal processing and sensor array signal processing, and applications in various areas. Offered 2013-14.
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 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 (4-0-8)
|
second, third terms
Prerequisites: EE 44 or equivalent.
Analysis and design of analog circuits at the transistor level. Emphasis on design-oriented 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, low-frequency behavior of single-stage and multistage amplifiers, current sources, active loads, differential amplifiers, operational amplifiers, high-frequency circuit analysis using time- and transfer constants, high-frequency 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: trans-linear circuits, switched capacitor circuits, data conversion circuits (A/D and D/A), continuous-time Gm.C filters, phase locked loops, oscillators, and modulators.
Instructor:
Hajimiri
EE/MedE 115
Micro-/Nano-scales Electro-Optics
9 units (3-0-6)
|
first term
Prerequisites: Introductory electromagnetic class and consent of the instructor.
The course will cover various electro-optical phenomena and devices in the micro-/nano-scales. We will discuss basic properties of light, imaging, aberrations, eyes, detectors, lasers, micro-optical components and systems, scalar diffraction theory, interference/interferometers, holography, dielectric/plasmonic waveguides, and various Raman techniques. Topics may vary.
Instructor:
Choo
ACM/EE 116
Introduction to Stochastic Processes and Modeling
9 units (3-0-6)
|
first term
Prerequisites: Ma 2, Ma 3 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:
Owhadi
EE 119 abc
Advanced Digital Systems Design
9 units (3-3-3) first, second term; 9 units (1-8-0) third term
|
first, second, third terms
Prerequisites: EE/CS 52 or CS/EE 181 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, 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. Not Offered: 2013-14
Instructor:
George
EE/MedE 124
Mixed-mode Integrated Circuits
9 units (3-0-6)
|
third term
Prerequisites: EE 45 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)
|
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 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. Not Offered 2013-14.
Instructor:
Staff
EE/Ma/CS 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 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 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, 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, turbo 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. Not offered 2013-14.
CS/EE/Ma 129 abc
Information and Complexity
9 units (3-0-6), first and second terms
|
(1-4-4) third term
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. Not offered 2013-14.
APh/EE 130
Electromagnetic Theory
9 units (3-0-6)
|
first term
Electromagnetic fields in vacuum: microscopic Maxwell's equations. Monochromatic fields: Rayleigh diffraction formulae, Huyghens principle, Rayleigh-Sommerfeld formula. The Fresnel-Fraunhofer approximation. Electromagnetic field in the presence of matter, spatial averages, macroscopic Maxwell equations. Helmholtz's equation. Group-velocity and group-velocity dispersion. Confined propagation, optical resonators, optical waveguides. Single mode and multimode waveguides. Nonlinear optics. Nonlinear propagation. Second harmonic generation. Parametric amplification.
Instructor:
Crosignani
EE/APh 131
Optical Wave Propagation
9 units (3-0-6)
|
second term
Light-matter 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, mode-locked lasers. Frequency combs in lasers. The spectral properties and coherence of laser light.
Instructor:
Yariv
APh/EE 132
Special Topics in Photonics and Optoelectronics
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:
Vahala
EE/CS/EST 135
Power System Analysis
9 units (3-0-6)
|
second term
Prerequisites: EE 44, Ma 2a, or equivalent.
Phasor representation, 3-phase transmission system, per-phase analysis; power system modeling, transmission line, transformer, generator; network matrix, power flow solution, optimal power flow; Swing equation, stability, protection; demand response, power markets.
Instructor:
Low
CS/EE 143
Communication Networks
9 units (3-3-3)
|
first term
Prerequisites: Ma 2, Ma 3, CS 24 and CS 38, or instructor permission.
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.
Instructor:
Low
CS/EE 144
The Ideas Behind Our Networked World
12 units (3-3-6)
|
second term
Prerequisites: Ma 2, Ma 3, CS 24 and CS 38, or instructor permission.
Social networks, the web, and the Internet are an essential parts of our lives and we all depend on them every day, but do you really know what makes them work? This course studies the "big" ideas behind our networked lives. Things like, 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 hands-on labs. This course can be combined with CS/EE 145 and CS 142 or CS/EE 143 to satisfy the project requirement for CS undergraduate degree, but CS/EE 143 and CS 142 are not required prerequisites. The course assumes students are comfortable with graph theory, probability, and basic programming.
Instructor:
Wierman
CS/EE 145
Projects in Networking
9 units (0-0-9)
|
third term
Prerequisites: Either CS/EE 144 or CS 141 b 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.
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, Ma 3 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. Not offered 2013-14.
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. EE 148a is not a prerequisite for EE 148b.
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. Part a not offered 2013-14; Part b offered 2013-14.
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)
|
third term
Prerequisites: EE 45.
Foundations of circuit theory-electric fields, magnetic fields, transmission lines, and Maxwell's equations, with engineering applications.
Instructor:
Yang
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/NB 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. Not offered 2013-14.
CS/CNS/EE 155
Probabilistic Graphical Models
9 units (3-3-3)
|
second term
Prerequisites: background in algorithms and statistics (CS/CNS/EE/NB 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. Not offered 2013-14.
CS/CNS/EE 156 ab
Learning Systems
9 units (3-0-6)
|
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:
Abu-Mostafa
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
Ge/EE/ESE 157 c
Remote Sensing for Environmental and Geological Applications
9 units (3-3-3)
|
third term
Use of different parts of the electromagnetic spectrum (visible, ultraviolet, infrared, and radio wavelengths) for interpretation of 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 multi-temporal studies. This course is complementary to EE 157ab with additional 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
CS/CNS/EE 159
Projects in Machine Learning and AI
9 units (0-0-9)
|
third term
Prerequisites: Two terms from the "Learning & Vision" project sequence.
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. Not offered 2013-14.
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. Given in alternate years; not offered 2013-14.
Instructor:
Hassibi
EE 163 ab
Communication Theory
9 units (3-0-6)
|
second, third terms
Prerequisites: EE 111; ACM/EE 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; signal-to-noise 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.
Instructor:
Ho
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. Given in alternate years; offered 2013-14.
Instructor:
Hassibi
EE/BE/MedE 166
Optical Methods for Biomedical Imaging and Diagnosis
9 units (3-1-5)
|
second 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. Given in alternate years; not offered 2013-14.
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. Not offered 2013-14.
EE/APh 180
Nanotechnology
6 units (3-0-3)
|
second 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
CS/EE 181 abc
VLSI Design Laboratory
12 units (3-6-3)
|
first, second 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. Part c not offered 2013-14.
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. Not offered 2013-14.
EE/BE/MedE 185
MEMS Technology and Devices
9 units (3-0-6)
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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. Not offered 2013-14.
CNS/Bi/EE/CS/NB 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; offered 2013-14.
EE/MedE 187
VLSI and ULSI Technology
9 units (3-0-6)
|
third 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. Not offered 2013-14.
BE/EE/MedE 189 ab
Design and Construction of Biodevices
12 units (3-6-3) a = third term
|
9 units (0-9-0) b = first term
Prerequisites: ACM 95 ab (for BE/EE/MedE 189 a); BE/EE/MedE 189 a (for BE/EE/MedE 189 b).
Part a, 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. Part b is a student-initiated design project requiring instructor's permission for enrollment. Enrollment is limited to 24 students. BE/EE/MedE 189 a is an option requirement; BE/EE/MedE 189 b is not.
Instructor:
Yang
ACM/CS/EE 218
Statistical Inference
3-0-6
|
third term
Prerequisites: ACM 104 and ACM 116, or instructor's permission.
Fundamentals of estimation theory and hypothesis testing; Bayesian and non-Bayesian approaches; minimax analysis, Cramer-Rao bounds, shrinkage in high dimensions; Kalman filtering, basics of graphical models; statistical model selection. Throughout the course, a computational viewpoint will be emphasized.
Instructor:
Chandrasekaran
EE 226
Advanced Information and Coding Theory
9 units (3-0-6)
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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. Not offered 2013-14.
EE 243 abc
Quantum Electronics Seminar
6 units (3-0-3)
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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. Not offered 2013-14.
CS/CNS/EE 253
Special Topics in Machine Learning
9 units (3-3-3)
Prerequisites: CS/CNS/EE/NB 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). Not offered 2013-14.
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:
May 1, 2024