A Brief Introduction to Numerical Analysis

Tyrtyshnikov Eugene E.

ISBN 10: 0817639160 / ISBN 13: 9780817639167

Published by Springer, 1997

About this Item

pp. 202. Seller Inventory # 18300552

Bibliographic Details

Title: A Brief Introduction to Numerical Analysis

Publisher: Springer

Publication Date: 1997

Binding: Hardcover

Condition: New

About this title

Synopsis:

This is an advanced textbook based on lectures given at the Moscow Physico-Technical Institute. The lectures are characterized by brevity, logical organization, and occasionally a lighthearted approach. It aims to involve the reader by asking questions, hinting, giving recommendations, comparing different methods, and discussing "optomistic" and "pessemistic" approaches to numerical analysis. Since matrix analysis underlies numerical analysis, this text emphasizes methods and algorithms of matrix analysis. Function approximations, methods of solving nonlinear equations, and minimization methods are also considered. As well as considering classical methods, new methods and approaches are discussed - such as spectral distribution theory and what it offers for design and proof of modern preconditioning strategies for large-scale linear algebra problems.

From the Back Cover:

This is an advanced textbook based on lectures delivered at the Moscow Physico-Technical Institute. Brevity, logical organization of the material, and a sometimes lighthearted approach are distinctive features of this modest book. The author makes the reader an active participant by asking questions, hinting, giving direct recommendations, comparing different methods, and discussing "pessimistic" and "optimistic" approaches to numerical analysis in a short time. Since matrix analysis underlies numerical methods and the author is an expert in this field, emphasis in the book is on methods and algorithms of matrix analysis. Also considered are function approximations, methods of solving nonlinear equations and minimization methods. Alongside classical methods, new results and approaches developed over the last few years are discussed - namely those on spectral distribution theory and what it gives for design and proof of modern preconditioning strategies for large-scale linear algebra problems. Advanced students and graduate students majoring in computer science, physics and mathematics will find this book helpful. It can be equally useful for advanced readers and researchers in providing them with new findings and new accessible views of the basic mathematical framework.