## EE 14N: Things about Stuff

Preference to freshmen. The stories behind disruptive inventions such as the telegraph, telephone, wireless, television, transistor, and chip are as important as the inventions themselves, for they elucidate broadly applicable scientific principles. Focus is on studying consumer devices; projects include building batteries, energy conversion devices and semiconductors from pocket change. Students may propose topics and projects of interest to them. The trajectory of the course is determined in large part by the students themselves.

Terms: Win
| Units: 3
| UG Reqs: GER:DB-EngrAppSci, WAY-SMA

Instructors:
Lee, T. (PI)

## 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 will 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

Instructors:
Ozgur, A. (PI)
;
Weissman, T. (PI)

## EE 26N: The Wireless World, and the Data You Leak

The world is increasingly based on wireless communication. Cell phones and WiFi are the most visible examples. Others are key fobs, water meters, gas and electric meters, garage door openers, baby monitors, and the list continues to expand. All of these produce RF signals you can detect and often decode. This seminar will explore how much information you broadcast throughout your day, and how it can easily be received and decoded using inexpensive hardware and public domain software. You will be able to explain why different information services use different frequencies, why they encode the information the way they do, and what security risks they present.

Terms: Win
| Units: 3

Instructors:
Pauly, J. (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, one-dimensional wave equation, electromagnetic waves, transmission lines, and one-dimensional resonators. Pre-requisites: none.

Terms: Spr, Sum
| Units: 5
| UG Reqs: GER:DB-EngrAppSci

Instructors:
Solgaard, O. (PI)
;
Vuckovic, J. (PI)

## EE 65: Modern Physics for Engineers

This course introduces the core ideas of modern physics that enable applications ranging from solar energy and efficient lighting to the modern electronic and optical devices and nanotechnologies that sense, process, store, communicate and display all our information. Though the ideas have broad impact, the course is widely accessible to engineering and science students with only basic linear algebra and calculus through simple ordinary differential equations as mathematics background. Topics include the quantum mechanics of electrons and photons (Schrödinger's equation, atoms, electrons, energy levels and energy bands; absorption and emission of photons; quantum confinement in nanostructures), the statistical mechanics of particles (entropy, the Boltzmann factor, thermal distributions), the thermodynamics of light (thermal radiation, limits to light concentration, spontaneous and stimulated emission), and the physics of information (Maxwell¿s demon, reversibility, entropy and noise in physics and information theory). Pre-requisite:
Physics 41. Pre- or co-requisite:
Math 53 or
CME 102.

Terms: Spr
| Units: 4
| UG Reqs: GER: DB-NatSci, GER:DB-EngrAppSci, WAY-SMA

Instructors:
Miller, D. (PI)

## EE 76: Information Science and Engineering

What is information? How can we measure and efficiently represent it? How can we reliably communicate and store it over media prone to noise and errors? How can we make sound decisions based on partial and noisy information? This course introduces the basic mathematics required to formulate and answer these questions, as well as some of the principles and techniques in the design of modern information, communication, and decision-making systems. Students will also get a glimpse of ways in which these principles manifest in domains ranging from the neural codes of the brain, through the genetic code, to the structure of human language.

Terms: Spr
| Units: 4

Instructors:
Ozgur, A. (PI)
;
Weissman, T. (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

Instructors:
Dutton, R. (PI)
;
Pauly, J. (PI)

## EE 101A: Circuits I

Introduction to circuit modeling and analysis. Topics include creating the models of typical components in electronic circuits and simplifying non-linear models for restricted ranges of operation (small signal model); and using network theory to solve linear and non-linear circuits under static and dynamic operations. Prerequisite: ENGR40 or ENGR40M is strongly recommended.

Terms: Win, Sum
| Units: 4
| UG Reqs: GER:DB-EngrAppSci, WAY-SMA

## EE 101B: Circuits II

Continuation of
EE101A. Introduction to circuit design for modern electronic systems. Modeling and analysis of analog gain stages, frequency response, feedback. Filtering and analog to digital conversion. Fundamentals of circuit simulation. Prerequisites:
EE101A,
EE102A. Recommended:
CME102.

Terms: Spr
| Units: 4
| UG Reqs: GER:DB-EngrAppSci, WAY-SMA

Instructors:
Murmann, B. (PI)

## EE 102A: Signal Processing and Linear Systems I

Concepts and tools for continuous- and discrete-time 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. Frequency-domain representations: Fourier series and Fourier transforms. Filtering and signal distortion. Time/frequency sampling and interpolation. Continuous-discrete-time signal conversion and quantization. Discrete-time signal processing. Prerequisite:
MATH 53 or
CME 102.

Terms: Win, Sum
| Units: 4
| UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR

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