Originally published: New York : McGraw-Hill, 1970.
Includes bibliographical references and indexes.
Chapter 1: Maximization, Minimization, and Motivation; Chapter 2: Vectors and Matrices; Chapter 3: Diagonalization and Canonical Forms for Symmetric Matrices; Chapter 4: Reduction of General Symmetric Matrices to Diagonal Form; Chapter 5: Constrained Maxima; Chapter 6: Functions of Matrices; Chapter 7: Variational Description of Characteristic Roots; Chapter 8: Inequalities; Chapter 9: Dynamic Programming; Chapter 10: Matrices and Differential Equations; Chapter 11: Explicit Solutions and Canonical Forms; Chapter 12: Symmetric Function, Kronecker Products and Circulants; Chapter 13: Stability Theory; Chapter 14: Markoff Matrices and Probability Theory; Chapter 15: Stochastic Matrices; Chapter 16: Positive Matrices, Perron's Theorem, and Mathematical Economics; Chapter 17: Control Processes; Chapter 18: Invariant Imbedding; Chapter 19: Numerical Inversion of the Laplace Transform and Tychonov Regularization; Appendix A: Linear Equations and Rank; Appendix B: The Quadratic Form of Selberg; Appendix C: A Method of Hermite; Appendix D: Moments and Quadratic Forms.
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Long considered to be a classic in its field, this was the first book in English to include three basic fields of the analysis of matrices -- symmetric matrices and quadratic forms, matrices and differential equations, and positive matrices and their use in probability theory and mathematical economics. Written in lucid, concise terms, this volume covers all the key aspects of matrix analysis and presents a variety of fundamental methods.