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No more than 6 credits of No more than 6 credits of These skills are developed through a variety of laboratory experiments including discrete semiconductor measurement, transistor amplifiers, motor control, and operational amplifier internals. The experiments develop practical skills through small design and soldering tasks. Finally, the course culminates in a two week group design project. In many ways this course is the laboratory of the co-requisite lecture course ECE 20002 Electrical Engineering Fundamentals II; however, we remind students that this is a standalone course that expects students will learn and demonstrate material not taught in other courses.For Fall 2018 and later catalog terms it is a CMPE Special Content Elective. No more than 6 credits of No more than 6 credits of Concurrent Prerequisites: basic circuit models for diodes, unipolar and bipolar transistors; design of small signal amplifiersDesign of biasing networks, small signal amplifiers and switching circuits.For Fall 2018 and later catalog terms it is a CMPE Special Content Elective. Discover everything Scribd has to offer, including books and audiobooks from major publishers. Start Free Trial Cancel anytime. Report this Document Download Now Save Save ECE Lab Manual For Later 0 ratings 0 found this document useful (0 votes) 197 views 29 pages ECE Lab Manual Uploaded by Anshu Singh Description: Full description Save Save ECE Lab Manual For Later 0 0 found this document useful, Mark this document as useful 0 0 found this document not useful, Mark this document as not useful Embed Share Print Download Now Jump to Page You are on page 1 of 29 Search inside document Browse Books Site Directory Site Language: English Change Language English Change Language.
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The department will endeavor to offer the coursesStudents are strongly advised to checkFor the namesTopics include circuit theory, assembly, and testing, embedded systems programming and debugging, transducer mechanisms and interfacing transducers, signals and systems theory, digital signal processing, and modular design techniques. Prerequisites: priority enrollment given to engineering majors EC04, EC26, EC27, EC28, and EC37. Techniques for using Matlab to graph the results of C computations are developed. Prerequisites: a familiarity with basic mathematics such as trigonometry functions and graphing is expected but this course assumes no prior programming knowledge. Key concepts include sampling, signal processing, communication, and real-time control. Students will apply their prior knowledge in C (from ECE15) to program microcontrollers and will engage in data analysis using the Python programming language. Prerequisites: MAE 8 or CSE 8B or CSE 11 or ECE 15. Prerequisites: CSE 8B or CSE 11 or ECE 15. Principles introduced in lectures are used in laboratory assignments, which also serve to introduce experimental and design methods.Topics include representation of information,Prerequisites: ECEMATH 20C and PHYS 2B must be taken concurrently. Program or materials fees may apply.Prerequisites: ECE 35. Topics will include two terminal devices, bipolar and field-effect transistors, and large and small signal analysis of diode and transistor circuits. (Program or materials fees may apply.) Prerequisites: ECE 35. Prerequisites: none. First-year student seminars are offered in all campus departments and undergraduate colleges, and topics vary from quarter to quarter. Enrollment is limited to fifteen to twenty students, with preference given to entering first-year students. Prerequisites: none. Typical subject areas are signal processing, VLSI design, electronic materials and devices, radio astronomy, communications, and optical computing. Prerequisites: none.
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Topics include frequency response; use of Laplace transforms; design and stability of filters using operational amplifiers. Integrated lab and lecture involves analysis, design, simulation, and testing of circuits and systems. Program or materials fees may apply. Prerequisites: ECE 45 and ECE 65. ECE 65 may be taken concurrently. Signal and system analysis in continuous and discrete time. Fourier series and transforms. Laplace and z-transforms. Linear Time Invariant Systems. Impulse response, frequency response, and transfer functions.Nonlinear device models for diodes, bipolar and field-effect transistors. Linearization of device models and small-signal equivalent circuits. Circuit designs will be simulated by computer and tested in the laboratory. Prerequisites: ECE 65 and ECE 100. ECE 100 can be taken concurrently. Semiconductor crystal structure, energy bands, doping, carrier statistics, drift and diffusion, p-n junctions, metal-semiconductor junctions. Bipolar junction transistors: current flow, amplification, switching, nonideal behavior. Metal-oxide-semiconductor structures, MOSFETs, device scaling. Prerequisites: ECE 65 and PHYS 2D or PHYS 4D and 4E. Electromagnetics ofRectangular waveguides. DielectricElectromagnetics of circuits.CMOS combinational logic, ratioed logic, noise margins, rise and fall delays, power dissipation, transmission gates. Short channel MOS model, effects on scaling. Sequential circuits, memory and array logic circuits. Three hours of lecture, one hour of discussion, three hours of laboratory. Prerequisites: ECE 25 or CSE 140, 45, and 65 and ECE 30 or CSE 30. Prerequisites: MATH 20A-B, MATH 20D, MATH 20C or MATH 31BH, and MATH 31AH or MATH 18. Problem sets and design exercises. A large-scale design project. Prerequisites: ECE 25 or CSE 140. Labs will culminate toward a fully functional robot prototype for demonstration. Prerequisites: ECE 16 or consent of instructor.
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Prerequisites: PHYSIt provides the fundamentals for advanced courses and engineering practice on electric power systems, smart grid, and electricity economics. The course requires implementing some of the computational techniques in simulation software. Prerequisites: ECE 35. Students may not receive credit for both ECE 121B and ECE 121. Prerequisites: ECE 121A. Antenna impedance, beam pattern, gain, and polarization. Dipoles, monopoles, paraboloids, phased arrays. Power and noise budgets for communication links. Atmospheric propagation and multipath.Control techniques such as vector control and direct torque control (DTC) of induction machines. Different control methods for direct current motors using different types of power converters, such as DC-DC and AC-DC converters. Design torque, speed, and position controller of DC motor drive. Prerequisites: ECE 121B and ECE 125A. Prerequisites: ECE 121A. Prerequisites: ECE 125A. Covers the same subjects that actual power system operators’ certification course covers. It systematically describes the vital grid operators’ functions and the processes required to operate the system. Uses actual case histories, and real examples of best in-class approaches from across the nation and the globe. Presents the problems encountered by operators and the enabling solutions to remedy them. Prerequisites: upper-division standing. Covers the practical aspects of the technologies, their design and system implementation. Topics include the changing nature of the grid with renewable resources, smart meters, synchrophasors (PMU), microgrids, distributed energy resources, and the associated information and communications infrastructures. Presents actual examples and best practices. Students will be provided with various tools. Prerequisites: ECE 35 and ECE 128A. Detailed explanations of the impacts of extreme weather and applicable industry standards and initiatives.
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Proven practices for successful restoration of the power grid, increased system resiliency, and ride-through after extreme weather providing real examples from around the globe. Prerequisites: ECE 128B. Analysis of dc and ac characteristics. Charge control model of dynamic behavior.Students will research, design, and develop an IOT device to serve an emerging market. Prerequisites: CSE 8B or CSE 11 or ECE 15. Students will research, design, and develop an IOT device to serve an emerging market. Prerequisites: ECE 140A. Students will gain broad experience using object-oriented methods and design patterns. Through increasingly difficult challenges, students will gain valuable real-world experience building, testing, and debugging software, and develop a robust mental model of modern software design and architecture. Prerequisites: CSE 30 or ECE 30. Topics include STL, design patterns, parsing, searching and sorting, algorithmic thinking, and design partitioning. The course will continue to explore best practices in software development, debugging, and testing. Prerequisites: ECE 141A. Students learn the underlying mechanics and implementation specifics of Python and how to effectively utilize the many built-in data structures and algorithms. The course introduces key modules for data analysis such as Numpy, Pandas, and Matplotlib. Participants learn to leverage and navigate the vast Python ecosystem to find codes and communities of individual interest. Prerequisites: ECE 16. Groups of students will build an elevator system from laser-cut and 3-D printed parts; integrate sensors, motors, and servos; and program using state-machine architecture in LabVIEW. Students will have the opportunity to take the National Instruments Certified LabVIEW Associate Developer (CLAD) exam at the end of the quarter. Program or materials fees may apply. Prerequisites: CSE 11 or CSE 8B or ECE 15. Transmissions, reflection, and scatteringAural and visual detection.
Prerequisites: ECEWorking in small teams, students will develop 1:8 scale autonomous cars that must perform on a simulated city track. Topics include robotics system integration, computer vision, algorithms for navigation, on-vehicle vs.Cross-listed with MAE 148. Students may not receive credit for ECE 148 and MAE 148. Program or materials fees may apply. Prerequisites: ECE 15 or ECE 35 or MAE 2 or MAE 3, and consent of instructor. Students learn how to think like entrepreneurs, pivot their ideas to match customer needs, and assess financial, market, and timeline feasibility. The end goal is an investor pitch and a business plan. Provides experiential education, encouragement, and coaching (“E3CE”) that prepares students for successful careers at start-up as well as large companies. Counts toward one professional elective only. Prerequisites: students must apply to enroll in order to gauge their past experience with and interest in entrepreneurship. Consent of instructor is required. Gaussian processes and linear transformation of Gaussian processes.Introduction to effects of intersymbol interference and fading. Detection and estimation theory, including optimal receiver design and maximum-likelihood parameter estimation. Renumbered from ECE 154B. Students may not receive credit for ECE 155 and ECE 154B. Prerequisites: ECE 101 or BENG 122A, ECE 109 or ECON 120A or MAE 108 or MATH 180A or MATH 180B or MATH 183 or MATH 186, and ECE 153. Undergraduate students must take a final exam; graduate students must write a term paper or complete a final project. Cross-listed with MAE 149 and SIO 238. Prerequisites: upper-division standing and consent of instructor, or graduate student in science and engineering. Flow control; prevention of deadlock and throughput degradation.Flow control; prevention of deadlock and throughput degradation.Renumbered from ECE 154C. Students may not receive credit for ECE 159 and ECE 154C. Prerequisites: ECE 153. Prerequisites: ECE 101.
Insensitive filter structures, lattice and waveA class project is required, algorithmsPrerequisites: ECEStability, sensitivity, bandwidth, compensation. Design of active filters. Switched capacitor circuits.Use of feedback and evaluation of noise performance. Parasitic effects of integrated circuit technology. Laboratory simulation and testing of circuits. ECE 163 recommended. Circuits for alternative logic styles and clocking schemes. Subsystems include ALUs, memory, processor arrays, and PLAs. Techniques for gate arrays, standard cell, and custom design. Design and simulation using CAD tools. Prerequisites: ECE 102. Impedance matching. DetectionDesign of transistor amplifiersCircuits designs will be simulated by computerTransient and steady-state behavior.CompensatorPrerequisites: ECETopics covered will include edge detection,Prerequisites: ECE. ECE 109 recommended. Introduction to nonlinear optimization. Applications to signal processing, system identification, robotics, and circuit design. Recommended preparation: ECE 143 (for Python) or equivalent proficiency in Matlab programming. Prerequisites: MATH 18 or MATH 31AH and ECE 15. Feature selection.Prerequisites: ECE 175A. Subject matter will not be repeated so it may be taken for credit more than once. Prerequisites: consent of instructor; department stamp. Ray transfer matrix, matrices of cascaded optics, numerical apertures of step and graded index fibers. Fresnel and Fraunhofer diffractions, interference of waves. Gaussian and Bessel beams, the ABCD law for transmissions through arbitrary optical systems. Spatial frequency, impulse response and transfer function of optical systems, Fourier transform and imaging properties of lenses, holography.Guided-wave optics: modes, losses, dispersion, coupling, switching. Fiber optics: step and graded index, single and multimode operation, attenuation, dispersion, fiber optic communications.Laser amplifiers and laser systems. Photodetection.
Electro-optics and acousto-optics, photonic switching.Prerequisites: MATHSubject matter will not be repeated so it may be taken for credit up to three times. Prerequisites: upper-division standing. Students will practice technical public speaking, including speeches with PowerPoint slides and speaker introductions, and presenting impromptu speeches. Students may not receive credit for both ECE 189 and ENG 100E. Prerequisites: upper-division standing. Written final report required. Prerequisites: students enrolling in this course must have completed all of the breadth courses and one depth course. The department stamp is required to enroll in ECE 190. (Specifications and enrollment forms are available in the undergraduate office.) All studentsPrerequisites: completionMust contain enough design to satisfy the ECE program’s four-unit design requirement. Must be taken for a letter grade. May extend over two quarters with a grade assigned at completion for both quarters. Prerequisites: admission to the ECE departmental honors program. Prerequisites: none. The final project consists of either a new project designed by the student team or extension of an existing project. The student teams also prepare a manual as part of their documentation of the final project. May be taken for credit two times. Prerequisites: BENG 1 or CENG 4 or CSE 11 or CSE 8B or ECE 5 or MAE 3 or NANO 4 or SE 1. Topics include energetics and dynamics of biological systems, physical factors of environment, and the kinetics of biological systems. Prerequisites: senior or graduate level standing. Prerequisites: senior or graduate level standing. Introduction to subthreshold conduction in MOS transistor and its similarities to biomolecular transport. Design of instrumentation amplifiers, sensors, and electrical stimulation interfaces. Transcutaneous wireless power transfer and electromagnetic effects on tissue. Recommended preparation: ECE 164 or BENG 186B or equivalent.
Prerequisites: senior or graduate level standing. The combination of statistics and algorithms produces statistical learning methods that automate the analysis of complex data. Such machine learning methods are widely used in systems biology and bioinformatics. This course provides an introduction to statistical learning and assumes familiarity with key statistical methods. Students may not receive credit for BNFO 285 and ECE 204 and BENG 285. Cross-listed with BNFO 285 and BENG 285. Prerequisites: ECE 271A or ECE 271B or MATH 283; graduate standing. Examples from optical imaging, CT, MR, ultrasound, nuclear, PET, and radiography. Cross-listed with BENG 280A. Renumbered from ECE 207. Students may receive credit for one of the following: ECE 207A or ECE 207 or BENG 280A. Prerequisites: graduate standing. We cover methods of broad use in many fields and apply them to biology, focusing on scalability to big genomic data. Topics include dynamic programming, continuous time Markov models, hidden Markov models, statistical inference of phylogenies, sequence alignment, uncertainty (e.g., bootstrapping), and heterogeneity (e.g., phylogenetic mixture models). Prerequisites: graduate standing. The combination of statistics and algorithms produces statistical learning methods that automate the analysis of complex data. Applications within the domain of neural engineering that utilize unsupervised and supervised generative statistical modeling techniques are explored. This course assumes familiarity with key statistical methods. Prerequisites: ECE 271A-B; graduate standing. Concepts from mathematical physics, quantum mechanics, quantum optics, and electromagnetic theory will be introduced as appropriate. Students may not receive credit for both ECE 212A and ECE 212AN. Prerequisites: graduate standing. Students may not receive credit forPrerequisites: ECENear-field localization effects and applications.
Students may not receive credit forPrerequisites: ECEDifferent kinds of magnetic materials. Magnetic phenomena including anisotropy, magnetostriction, domains, and magnetization dynamics. Current frontiers of nanomagnetics research including thin films and particles. Optical, data storage, and biomedical engineering applications of soft and hard magnetic materials. Prerequisites: graduate standing. Friis transmission and Radar equations, dipoles, loops, slots, ground planes, traveling wave antennas, array theory, phased arrays, impedance, frequency independent antennas, microstrip antennas, cell phone antennas, system level implications such as MIMO, multi-beam and phased array systems. Recommended preparation: ECE 107 or an equivalent undergraduate course in electromagnetics. Prerequisites: graduate standing. Topics covered include Maxwell’s equations,Prerequisites: ECEPractice in writingPrerequisites: ECEReflector andRecommended preparation: CE 222A, ECE 222B,The following topics will be covered: basics, convergence, estimation, and hypothesis testing. Python programs, examples, and visualizations will be used throughout the course. Prerequisites: graduate standing. This course develops the concept of universal probability that can be used as a proxy for the unknown distribution of data and provides a unified framework for several data science problems, including compression, portfolio selection, prediction, and classification. Prerequisites: ECE 225A or ECE 250; graduate standing. Participants will discuss selected topics including DNNs, CNNs, and RNNs in both supervised and unsupervised settings. Special emphasis will be on optimizing DL physical performance on different hardware platforms. The hardware platforms include CPU-CPU and CPU-GPU architectures. Prerequisites: ECE 250 or ECE 269 or ECE 271A; graduate standing.
The class will focus on both theoretical and empirical analysis performed on real data, including technological networks, social networks, information networks, biological networks, economic networks, and financial networks. Students will be exposed to a number of state-of-the-art software libraries for network data analysis and visualization via the Python notebook environment. Previous Python programming experience recommended. Prerequisites: graduate standing. To learn from data we use probability theory, which has been a mainstay of statistics and engineering for centuries. The class will focus on implementations for physical problems. Topics: Gaussian probabilities, linear models for regression, linear models for classification, neural networks, kernel methods, support vector machines, graphical models, mixture models, sampling methods, and sequential estimation. Prerequisites: graduate standing. Randomly assigned teams will learn to develop and deploy a data science product, write and document code in an ongoing process, produce corresponding user documentation and communicate product value verbally and in writing, and ultimately deploy and maintain products on a cloud platform. Recommended preparation: ECE 143. Prerequisites: ECE 225A or ECE 269, graduate standing. Course contentRecommendedPrerequisites: graduateComputer simulation of devices, scaling characteristics, high frequency performance, and circuit models. Prerequisites: ECE 230A; graduate standing. Band structures carrier scattering and recombination processes and their influence on transport properties will be emphasized. Recommended preparation: ECE 230A or equivalent. Prerequisites: ECE 230B; graduate standing. Starting with the fundamentals of CMOS scaling to nanometer dimensions, various advanced device and circuit concepts, including RF CMOS, low power CMOS, silicon memory, silicon-on-insulator, SiGe bipolar, strained silicon MOSFET’s, etc.Prerequisites: graduate standing.
Topics include epitaxial growth techniques, electrical properties of heterojunctions, transport and optical properties of quantum wells and superlattices. Prerequisites: ECE 230A; graduate standing. Radiative transition and nonradiative recombination. Laser, modulators, and photodetector devices will be discussed. Recommended preparation: ECE 230A and ECE 230C or equivalent. Prerequisites: ECE 236A; graduate standing. Operating principles of FETs and BJTs are reviewed, and opportunities for improving their performance with suitable material choices and bandgap engineering are highlighted. SiGe and III-V HBTs, III-V FETs, and current research areas are covered. Microwave characteristics, models and representative circuit applications. Recommended preparation: ECE 230B or equivalent course with emphasis on physics of solid-state electronic devices. Prerequisites: ECE 236B; graduate standing. Basic concepts, equilibrium properties of alloy systems, thermodynamic information from phase diagrams, surfaces and interfaces, crystalline defects. Cross-listed with Materials Science 201A and MAE 271A. Prerequisites: consent of instructor. Boltzman factor, homogeneous and heterogeneous reactions, solid state diffusion, Fick’s law, diffusion mechanisms, Kirkendall effects, Boltzmann-Manato analysis, high diffusivity paths. Cross-listed with Materials Science 201B and MAE 271B. Prerequisites: ECE 238A. Optical resonators, interferometry. Gaussian beam propagation and transformation. Laser oscillation and amplification, Q-switching and mode locking of lasers, some specific laser systems. Recommended preparation: ECE 107 and ECE 182 or equivalent, introductory quantum mechanics or ECE 183. Prerequisites: graduate standing. Optical computing and other applications. Recommended preparation: ECE 182 or equivalent. Prerequisites: ECE 240A; graduate standing. Electro-optical switching and modulation. Acousto-optical deflection and modulation. Detection theory.
Heterodyne detection, incoherent and coherent detection. Recommended preparation: ECE 181, ECE 183, or equivalent. Prerequisites: ECE 240B; graduate standing. Recommended preparation: ECE 240A, C. Prerequisites: graduate standing. Design, analysis, and applications of components (e.g., waveguides, microresonators, couplers, modulators, lasers, and detectors) for use in communications, sensing, metrology, and other areas. Prerequisites: ECE 241A; graduate standing. Analysis of thin and volume holograms, reflection and transmission holograms, color and polarization holograms. Optically recorded and computer-generated holography. Applications to information storage, optical interconnects, 2-D and 3-D display, pattern recognition, and image processing. Recommended preparation: ECE 182 or equivalent. Prerequisites: ECE 241B; graduate standing. RecommendedPrerequisites: ECELimits in photoelectric detection of light. RecommendedCross-listed with BENG 247A and NANO 247A. Prerequisites: graduate standing. Cross-listed with BENG 247B and NANO 247B. Prerequisites: graduate standing. Cross-listed with BENG 247C and NANO 247C. Prerequisites: graduate standing. Convergence in probability and in quadratic mean, Stochastic processes, stationarity. Processes with orthogonal and independent increments. Power spectrum and power spectral density. Stochastic integrals and derivatives. Spectral representation of wide sense stationary processes, harmonizable processes, moving average representations. Recommended preparation: ECE 153. Prerequisites: graduate standing. Coherence and transfer function estimation; model-based spectral estimation; linear prediction and AR modeling. Levinson-Durbin algorithm and lattice filters, minimum variance spectrum estimation. Cross-listed with SIO 207B. SIO 207A is intended for graduate students who have not had an undergraduate course in DSP.
Recommended preparation: ECE 153 or ECE 250, ECE 161A or ECE 251C, ECE 269 or equivalent, and SIO 207A or equivalent. Prerequisites: graduate standing. Cross-listed with SIO 207C. Prerequisites: graduatePrerequisites: graduate standing. Conventional and adaptive beamforming. Matched field processing. Sparse array design and processing techniques. Applications to acoustics, geophysics, and electromagnetics. Cross-listed with SIO 207D. Recommended preparation: ECE 251A. Prerequisites: graduate standing; ECE 251C (for ECE 251D); SIO 207C (for SIO 207D). Recommended preparation: ECE 161A. Prerequisites: graduatePrerequisites: ECERecommended preparation: ECERecommended preparation: ECE 153. Prerequisites: graduate standing. Recommended preparation: ECE 154A-B-C. Prerequisites: graduate standing. Students that have taken 255BN cannot take 255B for credit. Recommended preparation: ECE 250, and 259A or 259AN. Prerequisites: ECE 255A; graduate standing. Topics include background (information measures and typical sequences, point-to-point communication) and single-hop networks (multiple access channels, degraded broadcast channels, interference channels, channels with state, general broadcast channels, Gaussian vector channels, distributed lossless source coding, source coding with side information). Prerequisites: ECE 250; ECE 255B; graduate standing. Topics cover basic coding tools such as entropy coding, transform, and quantization as well as advanced coding methods: motion estimation and compensation, error resilient coding and scalable coding. Recommended preparation: Matlab programming. Prerequisites: graduate standing. Recommended preparation: ECE 158A. Prerequisites: graduate standing or consent of instructor. Topics to be covered include cellular approaches, call processing, digital modulation, MIMO technology, broadband networks, ad-hoc networks, and wireless packet access. Recommended preparation: ECE 159A and 154B, or equivalent. Prerequisites: graduate standing.
Topological structure,Elements of network. Decentralized operation, routeRecommended preparation: ECE 155. Prerequisites: ECE 250; graduate standing. Prerequisites: ECE 258A; graduate standing. Students who have taken ECE 259AN may not receive credit for ECE 259A. Prerequisites: graduate standing. Students who have taken ECE 259BN may not receive credit for ECE 259B. Recommended preparation: ECE 154A-B-C. Prerequisites: ECE 259A; graduate standing. Course contents vary by instructor. Example course topics: Coded-modulation for bandwidth-efficient data transmission; advanced algebraic and combinatorial coding theory; space-time coding for wireless communications; constrained coding for digital recording. Students who have taken ECE 259CN may not receive credit for ECE 259C. Prerequisites: ECEMOS transistor theory, circuit characterization, and performance estimation. CMOS logic design will be emphasized. Computer-aided design (CAD) tools for transistor level simulation, layout and verification will be introduced. Includes two hours of laboratory hours per week. Recommended preparation: undergraduate-level semiconductor electronics and digital system design, ECE 165 or equivalent. Prerequisites: graduate standing. Circuit building blocks including embedded memory and clock distribution. Computer-aided design (synthesis, place-and-route, verification) and performance analyses, and small-group block implementation projects spanning RTL to tape-out using leading-edge EDA tools. Cross-listed with CSE 241A. Recommended preparation: ECE 165. Prerequisites: ECEDifferent design alternatives are introduced and analyzed. Advanced design tools are used to design a hardware-software system. Class discussion, participation, and presentations of projects and special topics assignments are emphasized. Prerequisites: ECE 260B; graduate standing. Advanced feedback and stability analysis; compensation techniques. High-Performance CMOS operational amplifier topologies.