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Informationen zum Autor Ronald W. Shonkwiler is a Professor in the School of Mathematics at the Georgia Institute of Technology. He has authored or co-authored over 50 research papers in areas of functional analysis, mathematical biology, image processing algorithms, fractal geometry, neural networks and Monte Carlo optimization methods. His algorithm for monochrome image comparison is part of a US patent for fractal image compression. He has co-authored two other books, An Introduction to the Mathematics of Biology and The Handbook of Stochastic Analysis and Applications. Klappentext In this introductory text, the fundamental algorithms of numerical linear algebra are developed in a parallel context. Zusammenfassung In this introductory text! the fundamental algorithms of numerical linear algebra are developed in a parallel context. Topics include direct and iterative methods for solving linear systems! numerical methods for the eigenvector/eigenvalue problem and applications to Monte Carlo methods. Inhaltsverzeichnis Part I. Machines and Computation: 1. Introduction - the nature of high performance computation; 2. Theoretical considerations - complexity; 3. Machine implementations; Part II. Linear Systems: 4. Building blocks - floating point numbers and basic linear algebra; 5. Direct methods for linear systems and LU decomposition; 6. Direct methods for systems with special structure; 7. Error analysis and QR decomposition; 8. Iterative methods for linear systems; 9. Finding eigenvalues and eigenvectors; Part III. Monte Carlo Methods: 10. Monte Carlo simulation; 11. Monte Carlo optimization; Appendix: programming examples.
