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Introduction to Linear Dynamical Systems Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, lectures on regularized least squares and the Gauss-Newton method for the course, Introduction to Linear Dynamical Systems (EE263). Introduction to applied linear algebra and linear dynamical systems, with applications to circuits, signal processing, communications, and control systems. Topics include: Least-squares aproximations of over-determined equations and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm and singular value decomposition. Eigenvalues, left and right eigenvectors, and dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input multi-output systems, impulse and step matrices; convolution and transfer matrix descriptions. Complete Playlist for the Course: http://www.youtube.com/view_play_list?p=06960BA52D0DB32B EE 263 Course Website: http://www.stanford.edu/class/ee263/ Stanford University: http://www.stanford.edu/ Stanford University Channel on YouTube: http://www.youtube.com/stanford/

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Channels: Physics (General)

Tags: science electrical engineering technology linear dynamical system Gauss Newton method least squares recursive rank one update formula

Uploaded by: stanfordlinear ( Send Message ) on 29-08-2012. Dnatube suggest users to have interest in drug testing, mesothelioma, insurance, medical lawyers.

Duration: 75m 46s

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This video is a part of a lecture series from of Stanford University