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)
;
Bian, A. (TA)
;
Gomez, G. (TA)
;
Heywood, D. (TA)
;
Li, A. (TA)
;
Peltzer, O. (TA)
;
Suresh, I. (TA)
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)
;
Antin, B. (TA)
EE 133: Analog Communications Design Laboratory (EE 233)
Design, testing, and applications of Radio Frequency (RF) electronics: Amplitude Modulation (AM), Frequency Modulation (FM) and concepts of Software Define Radio (SDR) systems. Practical aspects of circuit implementations are developed; labs involve building and characterization of subsystems as well as integration of a complete radio system and a final project. Total enrollment limited to 25 students¿undergraduate and graduate levels. Prerequisite:
EE101B. Undergraduate students enroll in EE133 for 4 units and Graduate students enroll in EE233 for 3 units. Recommended:
EE114/214A.
Terms: Win

Units: 34

Grading: Letter or Credit/No Credit
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)
;
Zaman, M. (TA)
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 153: Power Electronics (EE 253)
Addressing the energy challenges of today and the environmental challenges of the future will require efficient energy conversion techniques. This course will discuss the circuits used to efficiently convert ac power to dc power, dc power from one voltage level to another, and dc power to ac power. The components used in these circuits (e.g., diodes, transistors, capacitors, inductors) will also be covered in detail to highlight their behavior in a practical implementation. A lab will be held with the class where students will obtain hands on experience with power electronic circuits. For WIM credit, students must enroll in
EE 153 for 4 units. No exceptions. Formerly
EE 292J. Prerequisite:
EE 101B.
Terms: Spr

Units: 34

UG Reqs: WAYSMA

Grading: Letter (ABCD/NP)
Instructors:
RivasDavila, J. (PI)
EE 155: Green Electronics (EE 255)
Many green technologies including hybrid cars, photovoltaic energy systems, efficient power supplies, and energyconserving control systems have at their heart intelligent, highpower electronics. This course examines this technology and uses greentech examples to teach the engineering principles of modeling, optimization, analysis, simulation, and design. Topics include power converter topologies, periodic steadystate analysis, control, motors and drives, photovoltaic systems, and design of magnetic components. The course involves a handson laboratory and a substantial final project. Formerly
EE 152. Required:
EE101B,
EE102A,
EE108. Recommended: ENGR40 or
EE122A.
Terms: not given this year

Units: 4

Grading: Letter or Credit/No Credit
EE 168: Introduction to Digital Image Processing
Computer processing of digital 2D and 3D data, combining theoretical material with implementation of computer algorithms. Topics: properties of digital images, design of display systems and algorithms, time and frequency representations, filters, image formation and enhancement, imaging systems, perspective, morphing, and animation applications. Instructional computer lab exercises implement practical algorithms. Final project consists of computer animations incorporating techniques learned in class. For WIM credit, students must enroll for 4 units. No exceptions. Prerequisite: Matlab programming.
Terms: Win

Units: 34

Grading: Letter or Credit/No Credit
Instructors:
Zebker, H. (PI)
;
Cornman, A. (TA)
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)
EE 180: Digital Systems Architecture
The design of processorbased digital systems. Instruction sets, addressing modes, data types. Assembly language programming, lowlevel data structures, introduction to operating systems and compilers. Processor microarchitecture, microprogramming, pipelining. Memory systems and caches. Input/output, interrupts, buses and DMA. System design implementation alternatives, software/hardware tradeoffs. Labs involve the design of processor subsystems and processorbased embedded systems. Formerly
EE 108B. Prerequisite:
CS107 (required) and
EE108 (recommended but not required).
Terms: Spr

Units: 4

UG Reqs: GER:DBEngrAppSci, WAYSMA

Grading: Letter or Credit/No Credit
Instructors:
Michelogiannakis, G. (PI)
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