Cartography, Dynamics - General & Miscellaneous, Neural Networks, Astrophysics & Space Science
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Overview
Topographic map formation is an important component of both artificial and biological networks, and is emerging as a key topic in the theory of Neural Networks, a popular area of artificial intelligence research. This book discusses in detail, the science behind a computer's ability to self-organize, an area which has important practical applications in data mining and pattern recognition. Written by a well-known researcher in the field and providing an introductory chapter to bring newcomers to the topic up-to-speed, this title provides complete coverage of self-organizing maps.Editorials
Booknews
Offers a unified survey of the field, focusing on current knowledge and available techniques for topographic map formation. Presents an information-based learning strategy for developing equiprobabilistic topographic maps, demonstrating how this approach yields faithful representations and how it can be successfully applied in such areas as density estimation, regression, clustering, and feature extraction. Begins with discussion of distortion-based learning, then examines the advantages of information-based learning techniques, and introduces a new algorithm for equiprobabilistic topographic map formation using neurons with kernel-based response characteristics. The author is an associate professor at the K. U. Leuven Medical School, Belgium, and a research associate at the Fund for Scientific Research, Belgium. Annotation c. Book News, Inc., Portland, OR (booknews.com)Book Details
Published
February 8, 2000
Publisher
New York : John Wiley & Sons, c2000.
Pages
288
Format
Hardcover
ISBN
9780471345077