lumped circuit abstraction
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Decomposition and abstraction through functions; introduction to recursion
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readInt() and readDouble(), The Division Operator w.r.t ints and Doubles, Order of Precedence for Operators, Type Casting, Shorthands, Constants, The Boolean Data Type, Value Comparisons, Boolean Expressions, Short Circuit Evaluation, Statement Blocks, Scope of Variables, Cascading if, The Switch Statement, The For Loop, The While Loop
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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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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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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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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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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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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
