## EE 263: Introduction to Linear Dynamical Systems (CME 263)

Applied linear algebra and linear dynamical systems with applications to circuits, signal processing, communications, and control systems. Topics: least-squares approximations of over-determined equations, and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm, and singular-value decomposition. Eigenvalues, left and right eigenvectors, with dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input/multi-output systems, impulse and step matrices; convolution and transfer-matrix descriptions. Control, reachability, and state transfer; observability and least-squares state estimation. Prerequisites: Linear algebra and matrices as in
EE 103 or
MATH 104; ordinary differential equations and Laplace transforms as in
EE 102B or
CME 102.

Terms: Aut, Sum
| Units: 3

Instructors:
Aggarwal, G. (PI)
;
Lall, S. (PI)

## EE 269: Signal Processing for Machine Learning

This course will introduce you to fundamental signal processing concepts and tools needed to apply machine learning to discrete signals. You will learn about commonly used techniques for capturing, processing, manipulating, learning and classifying signals. The topics include: mathematical models for discrete-time signals, vector spaces, Fourier analysis, time-frequency analysis, Z-transforms and filters, signal classification and prediction, basic image processing, compressed sensing and deep learning. This class will culminate in a final project. Prerequisites:
EE 102A and
EE 102B or equivalent, basic programming skills (Matlab).
EE 103 and
EE 178 are recommended.

Terms: Aut
| Units: 3

Instructors:
Pilanci, M. (PI)

## EE 271: Introduction to VLSI Systems

Provides a quick introduction to MOS transistors and IC fabrication and then creates abstractions to allow you to create and reason about complex digital systems. It uses a switch resistor model of a transistor, uses it to model gates, and then shows how gates and physical layout can be synthesized from Verilog or SystemVerilog descriptions. Most of the class will be spent on providing techniques to create designs that can be validated, are low power, provide good performance, and can be completed in finite time. Prerequisites: 101A, 108A and 108B; familiarity with transistors, logic design, Verilog and digital system organization

Terms: Aut
| Units: 3

Instructors:
Raina, P. (PI)

## EE 278: Introduction to Statistical Signal Processing

Review of basic probability and random variables. Random vectors and processes; convergence and limit theorems; IID, independent increment, Markov, and Gaussian random processes; stationary random processes; autocorrelation and power spectral density; mean square error estimation, detection, and linear estimation. Formerly
EE 278B. Prerequisites: EE178 and linear systems and Fourier transforms at the level of
EE102A,B or
EE261.

Terms: Aut, Sum
| Units: 3

Instructors:
Prabhakar, B. (PI)
;
Tolunay, M. (PI)

## EE 284: Introduction to Computer Networks

Structure and components of computer networks; functions and services; packet switching; layered architectures; OSI reference model; physical layer; data link layer; error control; window flow control; media access control protocols used in local area networks (Ethernet, Token Ring, FDDI) and satellite networks; network layer (datagram service, virtual circuit service, routing, congestion control, Internet Protocol); transport layer (UDP, TCP); application layer.

Terms: Aut
| Units: 3

Instructors:
Tobagi, F. (PI)

## EE 290A: Curricular Practical Training for Electrical Engineers

For EE majors who need work experience as part of their program of study. Final report required. Prerequisites: for 290B, EE MS and PhD students who have received a Satisfactory ("S") grade in
EE290A; for 290C, EE PhD degree candidacy and an "S" grade in
EE 290B; for 290D, EE PhD degree candidacy, an "S" grade in
EE 290C and instructor consent.

Terms: Aut, Win, Spr, Sum
| Units: 1

Instructors:
Osgood, B. (PI)
;
Tobagi, F. (PI)

## EE 290B: Curricular Practical Training for Electrical Engineers

For EE majors who need work experience as part of their program of study. Final report required. Prerequisites: for 290B, EE MS and PhD students who have received a Satisfactory ("S") grade in
EE290A; for 290C, EE PhD degree candidacy and an "S" grade in
EE 290B; for 290D, EE PhD degree candidacy, an "S" grade in
EE 290C and instructor consent.

Terms: Aut, Win, Spr, Sum
| Units: 1

Instructors:
Osgood, B. (PI)
;
Tobagi, F. (PI)

## EE 290C: Curricular Practical Training for Electrical Engineers

For EE majors who need work experience as part of their program of study. Final report required. Prerequisites: for 290B, EE MS and PhD students who have received a Satisfactory ("S") grade in
EE290A; for 290C, EE PhD degree candidacy and an "S" grade in
EE 290B; for 290D, EE PhD degree candidacy, an "S" grade in
EE 290C and instructor consent.

Terms: Aut, Win, Spr, Sum
| Units: 1

Instructors:
Osgood, B. (PI)
;
Tobagi, F. (PI)

## EE 290D: Curricular Practical Training for Electrical Engineers

Terms: Aut, Win, Spr, Sum
| Units: 1

Instructors:
Osgood, B. (PI)
;
Tobagi, F. (PI)

## EE 290E: Curricular Practical Training for Electrical Engineers

For EE majors who need work experience as part of their program of study. Final report required. Prerequisites: for 290B, EE MS and PhD students who have received a Satisfactory ("S") grade in
EE290A; for 290C, EE PhD degree candidacy and an "S" grade in
EE 290B; for 290D, EE PhD degree candidacy, an "S" grade in
EE 290C and instructor consent; for 290E, EE PhD degree candidacy, an "S" grade in
EE 290D and instructor consent.

Terms: Aut, Win, Spr, Sum
| Units: 1

Instructors:
Osgood, B. (PI)
;
Tobagi, F. (PI)

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