New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing (Studies in Fuzziness and Soft Computing) - Info and Reading Options
By Leszek Rutkowski

"New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing (Studies in Fuzziness and Soft Computing)" is published by Springer in March 19, 2004 - Berlin Heidelberg New York Hong Kong London Milano Paris Tokyo, it has 373 pages and the language of the book is English.
“New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing (Studies in Fuzziness and Soft Computing)” Metadata:
- Title: ➤ New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing (Studies in Fuzziness and Soft Computing)
- Author: Leszek Rutkowski
- Language: English
- Number of Pages: 373
- Publisher: Springer
- Publish Date: March 19, 2004
- Publish Location: ➤ Berlin Heidelberg New York Hong Kong London Milano Paris Tokyo
“New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing (Studies in Fuzziness and Soft Computing)” Subjects and Themes:
- Subjects: ➤ Soft computing - Neural networks (Computer science) - Informatique douce - Reseaux neuronaux (Informatique)
Edition Specifications:
- Format: Hardcover
- Weight: 1.5 pounds
- Dimensions: 9.2 x 6.1 x 0.9 inches
Edition Identifiers:
- The Open Library ID: OL9054451M - OL5290762W
- Online Computer Library Center (OCLC) ID: 53476946
- Library of Congress Control Number (LCCN): 2003064954
- ISBN-13: 9783540205845
- ISBN-10: 3540205845
- All ISBNs: 3540205845 - 9783540205845
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"New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing (Studies in Fuzziness and Soft Computing)" Description:
Open Data:
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. TOC:Probabilistic Neural Networks in a Non-stationary Environment.- Soft Computing Techniques for Image Compression.- Recursive Least Square Methods for Neural Network Learning and their Systolic Implementations
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