EE 25N: Science of Information
We live in the Information Age, but what is information, anyway? In 1948, Claude Shannon published a seminal paper formalizing our modern notion of information. Through lectures and lab visits, we'll learn how information can be measured and represented, why bits are the universal currency for information exchange, and how these ideas led to smartphones, the Internet, and more. We¿ll get a glimpse of information elements in other domains, including neural codes of the brain, cryptographic codes, genetic code, quantum information, and even entertainment. As a final project, students will create podcast episodes on one of the topics explored in the course.
Terms: Aut

Units: 4

Grading: Letter (ABCD/NP)
Instructors:
Ozgur Aydin, A. (PI)
;
Weissman, T. (PI)
EE 42: Introduction to Electromagnetics and Its Applications (ENGR 42)
Electricity and magnetism and its essential role in modern electrical engineering devices and systems, such as sensors, displays, DVD players, and optical communication systems. The topics that will be covered include electrostatics, magnetostatics, Maxwell's equations, onedimensional wave equation, electromagnetic waves, transmission lines, and onedimensional resonators. Prerequisites: none.
Terms: Win

Units: 5

UG Reqs: GER:DBEngrAppSci

Grading: Letter (ABCD/NP)
Instructors:
Solgaard, O. (PI)
;
Vuckovic, J. (PI)
EE 100: The Electrical Engineering Profession
Lectures/discussions on topics of importance to the electrical engineering professional. Continuing education, professional societies, intellectual property and patents, ethics, entrepreneurial engineering, and engineering management.
Terms: Aut

Units: 1

Grading: Satisfactory/No Credit
EE 101A: Circuits I
Introduction to circuit modeling and analysis. Topics include creating the models of typical components in electronic circuits and simplifying nonlinear models for restricted ranges of operation (small signal model); and using network theory to solve linear and nonlinear circuits under static and dynamic operations. Prerequisite: ENGR40 or ENGR40M is useful but not strictly required.
Terms: Win, Sum

Units: 4

UG Reqs: GER:DBEngrAppSci, WAYSMA

Grading: Letter or Credit/No Credit
Instructors:
Pop, E. (PI)
;
Wong, S. (PI)
EE 102A: Signal Processing and Linear Systems I
Concepts and tools for continuous and discretetime signal and system analysis with applications in signal processing, communications, and control. Mathematical representation of signals and systems. Linearity and time invariance. System impulse and step responses. System frequency response. Frequencydomain representations: Fourier series and Fourier transforms. Filtering and signal distortion. Time/frequency sampling and interpolation. Continuousdiscretetime signal conversion and quantization. Discretetime signal processing. Prerequisite:
MATH 53 or
CME 102.
Terms: Win, Sum

Units: 4

UG Reqs: GER:DBEngrAppSci, WAYAQR, WAYFR

Grading: Letter or Credit/No Credit
Instructors:
Kahn, J. (PI)
EE 103: Introduction to Matrix Methods (CME 103)
Introduction to applied linear algebra with emphasis on applications. Vectors, norm, and angle; linear independence and orthonormal sets; applications to document analysis. Clustering and the kmeans algorithm. Matrices, left and right inverses, QR factorization. Leastsquares and model fitting, regularization and crossvalidation. Constrained and nonlinear leastsquares. Applications include timeseries prediction, tomography, optimal control, and portfolio optimization. Undergraduate students should enroll for 5 units, and graduate students should enroll for 3 units. Prerequisites:
MATH 51 or
CME 100, and basic knowledge of computing (
CS 106A is more than enough, and can be taken concurrently).
EE103/CME103 and
Math 104 cover complementary topics in applied linear algebra. The focus of EE103 is on a few linear algebra concepts, and many applications; the focus of
Math 104 is on algorithms and concepts.
Terms: Aut, Win, Sum

Units: 35

UG Reqs: GER:DBMath, WAYAQR, WAYFR

Grading: Letter or Credit/No Credit
EE 108: Digital System Design
Digital circuit, logic, and system design. Digital representation of information. CMOS logic circuits. Combinational logic design. Logic building blocks, idioms, and structured design. Sequential logic design and timing analysis. Clocks and synchronization. Finite state machines. Microcode control. Digital system design. Control and datapath partitioning. Lab. *In Autumn, enrollment preference is given to EE majors. Any EE majors who must enroll in Autumn are invited to contact the instructor. Formerly
EE 108A.
Terms: Aut, Win

Units: 4

UG Reqs: GER:DBEngrAppSci, WAYAQR, WAYSMA

Grading: Letter or Credit/No Credit
Instructors:
Mitra, S. (PI)
EE 114: Fundamentals of Analog Integrated Circuit Design (EE 214A)
Analysis and simulation of elementary transistor stages, current mirrors, supply and temperatureindependent bias, and reference circuits. Overview of integrated circuit technologies, circuit components, component variations and practical design paradigms. Differential circuits, frequency response, and feedback will also be covered. Performance evaluation using computeraided design tools. Undergraduates must take
EE 114 for 4 units. Prerequisite: 101B. GER:DBEngrAppSci
Terms: Aut

Units: 34

UG Reqs: GER:DBEngrAppSci, WAYAQR, WAYSMA

Grading: Letter (ABCD/NP)
Instructors:
Arbabian, A. (PI)
;
Rekhi, A. (TA)
EE 118: Introduction to Mechatronics (ME 210)
Technologies involved in mechatronics (intelligent electromechanical systems), and techniques to apply this technology to mecatronic system design. Topics include: electronics (A/D, D/A converters, opamps, filters, power devices); software program design, eventdriven programming; hardware and DC stepper motors, solenoids, and robust sensing. Large, openended team project. Prerequisites:
ENGR 40,
CS 106, or equivalents.
Terms: Win

Units: 4

Grading: Letter (ABCD/NP)
Instructors:
Gumerlock, K. (PI)
;
Kenny, T. (PI)
EE 124: Introduction to Neuroelectrical Engineering
Fundamental properties of electrical activity in neurons, technology for measuring and altering neural activity, and operating principles of modern neurological and neural prosthetic medical systems. Topics: action potential generation and propagation, neuroMEMS and measurement systems, experimental design and statistical data analysis, information encoding and decoding, clinical diagnostic systems, and fullyimplantable neural prosthetic systems design. Prerequisite:
EE 101A and
EE 102A.
Terms: Win

Units: 3

UG Reqs: WAYSMA

Grading: Letter or Credit/No Credit
Instructors:
Shenoy, K. (PI)
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