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New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing : Studies in Fuzziness and Soft Computing - Leszek Rutkowski

New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing

Studies in Fuzziness and Soft Computing

Hardcover

Published: 3rd February 2004
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Science has made great progress in the twentieth century, with the establishment of proper disciplines in the fields of physics, computer science, molecular biology, and many others. At the same time, there have also emerged many engineering ideas that are interdisciplinary in nature, beyond the realm of such orthodox disciplines. These in­ clude, for example, artificial intelligence, fuzzy logic, artificial neural networks, evolutional computation, data mining, and so on. In or­ der to generate new technology that is truly human-friendly in the twenty-first century, integration of various methods beyond specific disciplines is required. Soft computing is a key concept for the creation of such human­ friendly technology in our modern information society. Professor Rutkowski is a pioneer in this field, having devoted himself for many years to publishing a large variety of original work. The present vol­ ume, based mostly on his own work, is a milestone in the devel­ opment of soft computing, integrating various disciplines from the fields of information science and engineering. The book consists of three parts, the first of which is devoted to probabilistic neural net­ works. Neural excitation is stochastic, so it is natural to investi­ gate the Bayesian properties of connectionist structures developed by Professor Rutkowski. This new approach has proven to be par­ ticularly useful for handling regression and classification problems vi Preface in time-varying environments. Throughout this book, major themes are selected from theoretical subjects that are tightly connected with challenging applications.

Introductionp. 1
Probabilistic neural networks in a non-stationary environmentp. 7
Kernel functions for construction of probabilistic neural networksp. 9
Introduction to probabilistic neural networksp. 21
General learning procedure in a time-varying environmentp. 59
Generalized regression neural networks in a time-varying environmentp. 73
Probabilistic neural networks for pattern classification in a time-varying environmentp. 135
Soft computing techniques for image compressionp. 168
Vector quantization for image compressionp. 169
The DPCM techniquep. 179
The PVQ schemep. 185
Design of the predictorp. 193
Design of the code-bookp. 203
Design of the PVQ schemesp. 217
Recursive least squares methods for neural network learning and their systolic implementationsp. 240
A family of the RLS learning algorithmsp. 241
Systolic implementations of the RLS learning algorithmsp. 283
Appendixp. 329
Referencesp. 343
Table of Contents provided by Blackwell. All Rights Reserved.

ISBN: 9783540205845
ISBN-10: 3540205845
Series: Studies in Fuzziness and Soft Computing
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 374
Published: 3rd February 2004
Publisher: Springer-Verlag Berlin and Heidelberg Gmbh & Co. Kg
Country of Publication: DE
Dimensions (cm): 23.4 x 15.6  x 2.54
Weight (kg): 1.6