Spectral approximations of linear operators

Spectral Approximation of Linear Operators offers in-depth coverage of properties of various types of operator convergence, the spectral approximation of non-self-adjoint operators, a generalization of classical perturbation theory, and computable errors bounds and iterative refinement techniques, along with many exercises (with solutions), making it a valuable textbook for graduate students and reference manual for self-study.

Audience: This book is appropriate for advanced undergraduate students and graduate students, researchers in functional and/or numerical analysis, and engineers who work on instability and turbulence. Contents: Chapter 1: The Matrix Eigenvalue Problem; Chapter 2: Elements of Functional Analysis: Basic Concepts; Chapter 3: Elements of Functional Analysis: Convergence and Perturbation Theory; Chapter 4: Numerical Approximation Methods for Integral and Differential Operators; Chapter 5: Spectral Approximation of a Closed Linear Operator; Chapter 6: Error Bounds and Localization Results for the Eigenelements; Chapter 7: Some Examples of Applications; Appendix: Discrete Approximation Theory