New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing
Authors: Rutkowski, Leszek
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This book presents new soft computing techniques for system modeling, pattern classification and image processing. The book consists of three parts, the first of which is devoted to probabilistic neural networks including a new approach which has proven to be useful for handling regression and classification problems in time-varying environments. The second part of the book is devoted to Soft Computing techniques for Image Compression including the vector quantization technique. The third part analyzes various types of recursive least square techniques for neural network learning as well as discussing hardware implemenations using systolic technology. By integrating various disciplines from the fields of soft computing science and engineering the book presents the key concepts for the creation of a human-friendly technology in our modern information society.
- Table of contents (14 chapters)
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Introduction
Pages 1-6
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Kernel Functions for Construction of Probabilistic Neural Networks
Pages 9-19
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Introduction to Probabilistic Neural Networks
Pages 21-57
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General Learning Procedure in a Time-Varying Environment
Pages 59-71
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Generalized Regression Neural Networks in a Time-Varying Environment
Pages 73-134
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Table of contents (14 chapters)
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書誌情報
- Bibliographic Information
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- Book Title
- New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing
- Authors
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- Leszek Rutkowski
- Series Title
- Studies in Fuzziness and Soft Computing
- Series Volume
- 143
- Copyright
- 2004
- Publisher
- Springer-Verlag Berlin Heidelberg
- Copyright Holder
- Springer-Verlag Berlin Heidelberg
- イーブック ISBN
- 978-3-540-40046-2
- DOI
- 10.1007/978-3-540-40046-2
- ハードカバー ISBN
- 978-3-540-20584-5
- ソフトカバー ISBN
- 978-3-642-05820-2
- Series ISSN
- 1434-9922
- Edition Number
- 1
- Number of Pages
- XI, 374
- Topics
