Ebook Free Best Approximation in Inner Product Spaces (CMS Books in Mathematics)
Ebook Free Best Approximation in Inner Product Spaces (CMS Books in Mathematics)
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Best Approximation in Inner Product Spaces (CMS Books in Mathematics)
Ebook Free Best Approximation in Inner Product Spaces (CMS Books in Mathematics)
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Review
From the reviews: MATHEMATICAL REVIEWS "This monograph contains the first comprehensive presentation of best approximation in inner product spaces (e.g., Hilbert spaces)…The author has succeeded very well in presenting clearly this first systematic study of best approximation in inner product spaces. The book is a valuable source for teaching graduate courses on approximation theory and related topics. Students with some basic knowledge in advanced calculus and linear algebra will be able to understand the text, which is written very smoothly. Since best approximation problems appear in many different branches, this monograph of about 300 pages will be a useful tool for researchers in mathematics, statistics, engineering, computer science and other fields of applications." F.R. Deutsch Best Approximation in Inner Product Spaces "The first comprehensive presentation of best approximation in inner product spaces." ― MATHEMATICAL REVIEWS "Nice introduction to inner-product spaces, with the particular application in mind. Discusses existence, uniqueness, characterization, and error of best approximations. Intended for graduate students, but mathematically sophisticated undergraduate could learn a lot from this book."― AMERICAN MATHEMATICAL MONTHLY "This monograph contains the first comprehensive presentation of best approximation in inner product spaces … . Moreover, at the end of each chapter there is a section with numerous exercises and one with notes in which the results are considered in a historical perspective. The author has succeeded very well in presenting clearly his first systematic study of approximation in inner product spaces. The book is a valuable source for teaching graduate courses … ." (Günther Nürnberger, Mathematical Reviews, Issue 2002 c) "Nice introduction to inner-product spaces, with the particular application in mind. Discusses existence, uniqueness, characterization, and error of best approximations. Intended for graduate students, but mathematically sophisticated undergraduates could learn a lot from this book. Twelve chapters, with exercise sets and historical notes." (American Mathematical Monthly, August-September, 2002) "The central concern of this book is the best approximation problem … . As an introduction to approximation theory, this book serves quite well. The background required is just basic analysis and linear algebra, a number of important topics are covered and the explanations are clear. Each chapter ends with a variety of exercises and detailed historical remarks. It has well been proofread … . I think this book is destined to serve a number of purposes." (David Yost, The Australian Mathematical Society Gazette, Vol. 29 (2), 2002) "This is an interesting and intriguing book, and to that extent it is already a success. Its principal aim is pedagogical; it is ‘the book of the course’ which the author has offered at the Pennsylvania State University for a number of years … . Each chapter is liberally supplied with exercises, the book contains a wealth of material and is a pleasure to read." (A. L. Brown, Zentralblatt MATH, Vol. 980, 2002) "The book is based on a graduate course on Best Approximation taught by the author for over twenty five years at the Pennsylvania State University. … Each chapter ends with a set of exercises and very interesting historical notes. Written by a well-known specialist in best approximation theory, the book contains a good treatment of best approximation in inner product spaces and can be used as a textbook for graduate courses or for self-study." (Stefan Cobzas, Studia Universitatis Babes-Bolyai Mathematica, Vol. XLVII (2), 2002) "This is a very nice book on approximation that can serve as a basis for course material, as well as for independent study. It is very nicely written, and … it takes the reader through many different fields and to considerable depth. … many pictures help the reader to comprehend the ideas and concepts. The book contains many examples and counterexamples … . I have found the problem section very interesting, and they are certainly very useful for students who are just learning the material." (Vilmos Totik, Acta Scientiarum Mathematicarum, Vol. 68, 2002)
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Product details
Series: CMS Books in Mathematics (Book 7)
Hardcover: 338 pages
Publisher: Springer; 2001 edition (April 20, 2001)
Language: English
ISBN-10: 0387951563
ISBN-13: 978-0387951560
Product Dimensions:
6.1 x 0.8 x 9.2 inches
Shipping Weight: 1.6 pounds (View shipping rates and policies)
Average Customer Review:
5.0 out of 5 stars
2 customer reviews
Amazon Best Sellers Rank:
#1,862,715 in Books (See Top 100 in Books)
Frank Deutsch writes this remarkably self-contained work on the most fundamental aspects of approximation theory in vector spaces with inner products.Deutsch starts this work by describing the basic problems of approximation theory: what is the best line fit (linear regression), what is the best solution to an over-determined system of equations, how to approximate a real continuous function with a polynomial, how to solve basic control system problems, and computing the best approximation to a surface with convexity constraints. He simply explains how to characterize and solve these problems with approximation theory while gently introducing graduate level analysis. The reader will learn the basics of orthogonality, Hilbert Spaces, compactness, dual spaces, Fourier analysis, Gram-Schmidt orthonormalization, Zorn's Lemma, and dual spaces with applications of all these concepts to concrete approximation problems. He concludes the text with four chapters of very recent research on common computer algorithms, strong CHIP, and the convexity of Chebyshev Sets. This book is a great introduction to approximation theory and modern analysis. I highly recommend it to any advanced undergraduate mathematics student or to any graduate student studying operations research, electrical engineering, or computer science (esp. numerical analysis).
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