"Lec 7 - Convex Optimization I" Professor Stephen Boyd, of the Stanford University Electrical Engineering department, expands upon his previous lectures on convex optimization problems for the course, Convex Optimization I (EE 364A). Convex Optimization I concentrates on recognizing and solving convex optimization problems that arise in engineering. 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. Interior-point methods. Applications to signal processing, control, digital and analog circuit design, computational geometry, statistics, and mechanical engineering. Complete Playlist for the Course: http://www.youtube.com/view_play_list?p=3940DD956CDF0622 EE 364A Course Website: http://www.stanford.edu/class/ee364 Stanford University: http://www.stanford.edu/ Stanford University Channel on YouTube: http://www.youtube.com/stanford/

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Channels: Physics (General) Mathematics

Tags: science electrical engineering technology convex optimization generalized inequality constraints minimization risk return eigenvalue linear matrix Pareto optimal

Uploaded by: stanfordconopt ( Send Message ) on 03-09-2012.

Duration: 74m 38s

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