Introduction to Matrix Analysis |
Contents
Maximization Minimization and Motivation | 1 |
Vectors 12 Vector Addition 13 Scalar Multiplication | 16 |
Diagonalization and Canonical Forms for Symmetric Matrices | 32 |
Copyright | |
24 other sections not shown
Other editions - View all
Common terms and phrases
a₁ algebraic analytic b₁ Bellman c₁ 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 dx dt elements exists follows foregoing functional equation given Hence Hermitian matrix inequality integral Kronecker Kronecker product Ky Fan linear equations linear systems linearly independent Markoff matrix mathematical matrix theory minimum MISCELLANEOUS EXERCISES multiple N-dimensional 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 result satisfying scalar sequence Show skew-symmetric matrix stability stochastic sufficient condition symmetric matrices Taussky techniques Theorem transformation unitary unitary matrix variables x,Ax yields zero λε λι