Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 392 pp. Englisch. N� de r�f. du vendeur 9783540205845

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New Soft Computing Techniques for System Modeling, Pattern Classification and Image Processing (Studies in Fuzziness and Soft Computing, 143)

Rutkowski, Leszek

Edit� par Springer, 2004

ISBN 10 : 3540205845 ISBN 13 : 9783540205845

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Etat : New. N� de r�f. du vendeur I-9783540205845

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

Leszek Rutkowski

Edit� par Springer Berlin Heidelberg, 2004

ISBN 10 : 3540205845 ISBN 13 : 9783540205845

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. New Soft Computing Techniques for System Modeling, Pattern Classification, Image ProcessingWritten by a pioneer in the field of human-friendly technologyScience has made great progress in the twentieth century, with the establishment of pr. N� de r�f. du vendeur 4884720

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

Leszek Rutkowski

Edit� par Springer Berlin Heidelberg, 2004

ISBN 10 : 3540205845 ISBN 13 : 9783540205845

Neuf Couverture rigide

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. N� de r�f. du vendeur 9783540205845

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