lumped circuit abstraction
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Abstract Data Types, Wall of Abstraction, Why ADTs?, Live Coding Example: Creating the Vector Class, Private Data Members, Growing Dynamically: Making Space at Runtime, Insert and Remove Functions, Templatizing the Class Created, Including the "template.cpp" - Why?
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The course covers the system and design issues relevant to high-speed electrical (and optical, if time permits) signaling. We start with the basics of channel properties, modeling, measurements, and communications techniques. Circuit design of main components is covered in detail. The system design issues such as planning and budgeting are presented. A large portion of the class is devoted to case studies that include the multi...more
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Architectural and circuit level design and analysis of integrated analog-to-digital and digital-to-analog interfaces in CMOS and BiCMOS VLSI technology. Analog-digital converters, digital-analog converters, sample/hold amplifiers, continuous and switched-capacitor filters. RF integrated electronics including synthesizers, LNA's, and baseband processing. Low power mixed signal design. Data communications functions including clock recovery. ...more
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Jennifer Raymond (Stanford University) is building a "wiring diagram" for the brain. By bridging the gap between individual synapses and whole-brain learning & memory, Raymond's research offers new insights and strategies for medical rehabilitation and K-12 education.
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This course is designed to serve as a first course in an undergraduate electrical engineering (EE), or electrical engineering and computer science (EECS) curriculum. The course introduces the fundamentals of the lumped circuit abstraction. Topics covered include: resistive elements and networks; independent and dependent sources; switches and MOS transistors; digital abstraction; amplifiers; energy storage elements; dynamics of first- ...more
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Programming Methodology is the largest of the introductory programming courses and is one of the largest courses at Stanford. Topics focus on the introduction to the engineering of computer applications emphasizing modern software engineering principles: object-oriented design, decomposition, encapsulation, abstraction, and testing. Programming Methodology teaches the widely-used Java programming language along with good software engine...more
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Note: This course is being offered by Stanford this summer as an online course for credit. It can be taken individually, or as part of a master’s degree or graduate certificate earned online through the Stanford Center for Professional Development. This course is the natural successor to Programming Methodology and covers such advanced programming topics as recursion, algorithmic analysis, and data abstraction using the C++ programming...more
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Concentrates on recognizing and solving convex optimization problems that arise in engineering. Topics include: Convex sets, functions, and optimization problems. Basics of convex analysis. Least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems. Optimality conditions, duality theory, theorems of alternative, and applications. Interiorpoint methods. Applications to signal proc...more
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Continuation of Convex Optimization I. Topics include: Subgradient, cutting-plane, and ellipsoid methods. Decentralized convex optimization via primal and dual decomposition. Alternating projections. Exploiting problem structure in implementation. Convex relaxations of hard problems, and global optimization via branch & bound. Robust optimization. Selected applications in areas such as control, circuit design, signal processing, and com...more
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Decomposition and abstraction through functions; introduction to recursion
