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.
• Control, reachability, state transfer, and least-norm inputs.
• Observability and least-squares state estimation.

Prerequisites:

• Exposure to linear algebra and matrices (as in Math. 103).
• You should have seen the following topics: matrices and vectors, (introductory) linear algebra; differential equations, Laplace transform, transfer functions.
• Exposure to topics such as control systems, circuits, signals and systems, or dynamics is not required, but can increase your appreciation.

Course Homepage: http://see.stanford.edu/see/courseinfo.aspx?coll=17005383-19c6-49ed-9497-2ba8bfcfe5f6

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