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:
Lee, T. (PI)
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:DBEngrAppSci, WAYSMA

Grading: Letter or Credit/No Credit
Instructors:
Murmann, B. (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 102B: Signal Processing and Linear Systems II
Continuation of
EE 102A. Concepts and tools for continuous and discretetime signal and system analysis with applications in communications, signal processing and control. Analog and digital modulation and demodulation. Sampling, reconstruction, decimation and interpolation. Finite impulse response filter design. Discrete Fourier transforms, applications in convolution and spectral analysis. Laplace transforms, applications in circuits and feedback control. Z transforms, applications in infinite impulse response filter design. Prerequisite:
EE 102A.
Terms: Spr

Units: 4

UG Reqs: GER:DBEngrAppSci, WAYAQR, WAYFR

Grading: Letter or Credit/No Credit
Instructors:
Pauly, J. (PI)
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
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

Grading: Letter (ABCD/NP)
Instructors:
Arbabian, A. (PI)
EE 116: Semiconductor Devices for Energy and Electronics
The underpinnings of modern technology are the transistor (circuits), the capacitor (memory), and the solar cell (energy).
EE 116 introduces the physics of their operation, their historical origins (including Nobel prize breakthroughs), and how they can be optimized for future applications. The class covers physical principles of semiconductors, including silicon and new material discoveries, quantum effects, band theory, operating principles, and device equations. Recommended (but not required) corequisite:
EE 65 or equivalent.
Terms: Spr

Units: 3

UG Reqs: GER:DBEngrAppSci

Grading: Letter or Credit/No Credit
Instructors:
Pop, E. (PI)
EE 134: Introduction to Photonics
Photonics, optical components, and fiber optics. Conceptual and mathematical tools for design and analysis of optical communication, sensor and imaging systems. Experimental characterization of semiconductor lasers, optical fibers, photodetectors, receiver circuitry, fiber optic links, optical amplifiers, and optical sensors. Class project on confocal microscopy or other method of sensing or analyzing biometric data. Laboratory experiments. Prerequisite:
EE 102A and one of the following:
EE 42,
Physics 43, or
Physics 63.
Terms: Win

Units: 4

UG Reqs: GER:DBEngrAppSci

Grading: Letter (ABCD/NP)
Instructors:
Hesselink, L. (PI)
EE 142: Engineering Electromagnetics
Introduction to electromagnetism and Maxwell's equations in static and dynamic regimes. Electrostatics and magnetostatics: Gauss's, Coulomb's, Faraday's, Ampere's, BiotSavart's laws. Electric and magnetic potentials. Boundary conditions. Electric and magnetic field energy. Electrodynamics: Wave equation; Electromagnetic waves; Phasor form of Maxwell's equations.nSolution of the wave equation in 1D free space: Wavelength, wavevector, forward and backward propagating plane waves.Poynting's theorem. Propagation in lossy media, skin depth. Reflection and refraction at planar boundaries, total internal reflection. Solutions of wave equation for various 1D3D problems: Electromagnetic resonators, waveguides periodic media, transmission lines. Formerly
EE 141. Prerequisites: Phys 43 or
EE 42,
CME 100,
CME 102 (recommended)
Terms: Spr

Units: 3

UG Reqs: GER:DBEngrAppSci, WAYFR, WAYSMA

Grading: Letter (ABCD/NP)
Instructors:
Fan, J. (PI)
EE 178: Probabilistic Systems Analysis
Introduction to probability and statistics and their role in modeling and analyzing real world phenomena. Events, sample space, and probability. Discrete random variables, probability mass functions, independence and conditional probability, expectation and conditional expectation. Continuous random variables, probability density functions, independence and expectation, derived densities. Transforms, moments, sums of independent random variables. Simple random processes. Limit theorems. Introduction to statistics: significance, estimation and detection. Prerequisites: basic calculus.
Terms: Spr

Units: 4

UG Reqs: GER:DBEngrAppSci

Grading: Letter or Credit/No Credit
Instructors:
Ozgur Aydin, A. (PI)
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