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Introduction to Matrix Analysis (Classics in Applied Mathematics)

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Introduction to Matrix Analysis (Classics in Applied Mathematics)

I have been using this book for many years as a reference and as a source of interesting diversions. Bellman's typically dense style and leaving some proofs to the reader makes for a lot more material than its 387 pages would indicate. The main topics begin with matrix theory in maxima and minima and quickly get to dynamic programming, differential equations, and stability theory. This is the one good reference I have found on Markov matrices (not Markov processes). The last few topics are control processes, invariant imbedding, and Tychonov regularization. Side topics include Vandermonde matrices, Gaussian quadrature, and much, much more.
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