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/
Video is embedded from external source so download is not available.
Channels: Physics (General)
Duration: 75m 46s
No content is added to this lecture.
This video is a part of a lecture series from of Stanford University