## Introduction to matrix analysis |

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### Contents

Maximization Minimization and Motivation | 1 |

Vectors and Matrices | 12 |

Diagonalization and Canonical Forms for Symmetric Matrices | 32 |

Copyright | |

17 other sections not shown

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### Common terms and phrases

algebraic analysis analytic Bellman Cayley-Hamilton theorem Chap characteristic roots characteristic values characteristic vector associated coefficients column commute complex components Consider convergence defined denote derive determinantal diagonal form discussion distinct characteristic roots Duke Math elements establish exists follows functional equation given Hence Hermitian Matrices Hermitian matrix inductive inequality integral Kronecker Kronecker products Ky Fan linear equations linear systems linearly independent Markoff matrix mathematical matrix theory method minimum MISCELLANEOUS EXERCISES multiple N X N necessary and sufficient non-negative definite nonsingular nonsingular matrix nonzero notation obtain orthogonal matrix polynomial positive definite probability vector problem of determining Proc proof quadratic form quantities real symmetric recurrence relation representation roots and vectors satisfying scalar sequence Show skew-symmetric matrix stability stochastic sufficient condition symmetric matrices Taussky techniques Theorem tion unitary unitary matrix variables write x,Ax Xi(n yields zero