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Vector Space Projections: A Numerical Approach to Signal and Image Processing, Neural Nets, and Optics
 
 
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Vector Space Projections: A Numerical Approach to Signal and Image Processing, Neural Nets, and Optics [Hardcover]

Henry Stark (Author), Yongyi Yang (Author)
5.0 out of 5 stars  See all reviews (1 customer review)

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Book Description

0471241407 978-0471241409 February 27, 1998 1
A guide to the theory and application of methods of projections.

With the rise of powerful personal computers, methods of vector space projections have moved rapidly from the realm of theory into widespread use. This book reflects the growing interest in the application of these methods to problem solving in science and engineering. It brings together material previously scattered in disparate papers, book chapters, and articles, and offers a systematic treatment of vector space projections.

Written by two leading authorities in the field, this self-contained volume provides a tutorial on projection methods and how to apply them in science and engineering. It details effective problem-solving strategies, and explores key applications in communication and signal processing, neural networks and pattern recognition, and optics and image processing. This book:
* Reviews the fundamentals of vector space theory
* Covers principles and applications of vector space projections in general, and projections onto convex sets in particular
* Provides real-world examples solvable on PCs and modest workstations
* Features more than 100 illustrations
* Includes end-of-chapter exercises and references.


This extremely useful reference for practicing engineers, scientists, and educators can also be used for graduate-level study in science, mathematics, and engineering. Portions of the book have been used as material in short courses on applications of vector space projections.

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Editorial Reviews

Review

"...a very useful addition among classical signal processing texts...it can be warmly recommended..." (Analog Dialogue, Vol. 36, No. 5, September-October 2002)

From the Publisher

This book deals with the theory and applications of a mathematical technique known as "projections onto convex sets" which is used for solving problems in science and engineering. The material applies to all branches of science and engineering.

Product Details

  • Hardcover: 408 pages
  • Publisher: Wiley-Interscience; 1 edition (February 27, 1998)
  • Language: English
  • ISBN-10: 0471241407
  • ISBN-13: 978-0471241409
  • Product Dimensions: 9.6 x 6.4 x 1 inches
  • Shipping Weight: 1.4 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #1,995,510 in Books (See Top 100 in Books)

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11 of 11 people found the following review helpful:
5.0 out of 5 stars The only book on this important subject in print, November 17, 1999
By A Customer
This review is from: Vector Space Projections: A Numerical Approach to Signal and Image Processing, Neural Nets, and Optics (Hardcover)
This book showed me how vector space methods are a natural way to use the computer for solving difficult problems in engineering design. Although my background in mathematics consists only of advanced calculus and linear algebra, I had no trouble following the theory and learning the applications. For electrical engineers, such as myself, the applications to digital filter design were particularly interesting. There are many other applications described, including the design of lenses, image processing, even neural nets. What I like is that the authors give the backgroud to each application so that even if you are unfamiliar with the field, there are clear and concise introductions that help your understanding of the problem. For example, in the digital filter design section, the authors explain why digital filters are important and how they relate to analog filters. To write a book like this takes not only broad knowledge but extraordinary expository skills.
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Inside This Book (learn more)
First Sentence:
In this chapter we provide some basic concepts and results pertaining to linear vector spaces. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
relaxed projector, generalized projection algorithm, detector footprint, generalized projections algorithm, convex projection algorithm, misclassification history, sequential projection algorithm, error reduction property, phase retrieval problem, minimum distance property, vector space projections, library vectors, convex projections, quantized samples, linear variety, diffractive element, image recovery, blocking artifacts, interconnection matrix, detector readings, obeys property, closed convex set, image restoration, phase profile, projection methods
Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Academic Press, John Wiley, Englewood Cliffs, Circuits Syst, Rensselaer Polytechnic Institute, Illinois Institute of Technology, Optica Acta, Signal Process
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