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

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

Leszek Rutkowski - Collection Studies in Fuzziness and Soft Computing

373 pages, parution le 16/02/2004

Résumé

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 implementations 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.

Written for:
Engineers, researchers and graduated students Soft Computing and Computer Science

Sommaire

  • Introduction
  • I Probabilistic Neural Networks in a Non-stationary Environment
    • Kernel Functions for Construction of Probabilistic Neural Networks
    • Introduction to Probabilistic Neural Networks
    • General Learning Procedure in a Time-Varying Environment
    • Generalized Regression Neural Networks in a Time-Varying Environment
    • Probabilistic Neural Networks for Pattern Classi…cation in a Time-Varying Environment
  • II Soft Computing Techniques for Image Compression
    • Vector Quantization for Image Compression
    • The DPCM Technique
    • The PVQ Scheme
    • Design of the Predictor
    • Design of the Code-book
    • Design of the PVQ Schemes
    • Recursive Least Squares Methods for Neural Network Learning and their Systolic Implementations
    • A Family of the RLS Learning Algorithms
    • Systolic Implementations of the RLS Learning Algorithms
    • Appendix
    • References
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Caractéristiques techniques

  PAPIER
Éditeur(s) Springer
Auteur(s) Leszek Rutkowski
Collection Studies in Fuzziness and Soft Computing
Parution 16/02/2004
Nb. de pages 373
Format 16 x 24
Couverture Relié
Poids 690g
Intérieur Noir et Blanc
EAN13 9783540205845

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