9781852333522 - pattern classification: neuro-fuzzy methods and their comparison di abe, shigeo (8 risultati)
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Da: Phatpocket Limited, Waltham Abbey, HERTS, Regno UnitoPhatpocket Limited
Contatta il venditoreVenditore con 5 stelleCondizione: Usato - Buono
EUR 96,77
EUR 12,40 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Condizione: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 145,89
EUR 3,42 spedizioneSpedito in U.S.A.Quantità: 4 disponibili
Condizione: New. pp. 352.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 114,36
EUR 63,47 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Neural networks have a learning capability but analysis of a trained network is difficult. On the other hand, extraction of fuzzy rules is difficult but once they have been extracted, it is relatively easy to analyze the fuzzy system. This book solves th…e above problems by developing new learning paradigms and architectures for neural networks and fuzzy systems.The book consists of two parts: Pattern Classification and Function Approximation. In the first part, based on the synthesis principle of the neural-network classifier: A new learning paradigm is discussed and classification performance and training time of the new paradigm for several real-world data sets are compared with those of the widely-used back-propagation algorithm; Fuzzy classifiers of different architectures based on fuzzy rules can be defined with hyperbox, polyhedral, or ellipsoidal regions. The book discusses the unified approach for training these fuzzy classifiers; The performance of the newly-developed fuzzy classifiers and the conventional classifiers such as nearest-neighbor classifiers and support vector machines are evaluated using several real-world data sets and their advantages and disadvantages are clarified.In the second part: Function approximation is discussed extending the discussions in the first part; Performance of the function approximators is compared.This book is aimed primarily at researchers and practitioners in the field of artificial intelligence and neural networks.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 106,99
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Neural networks have a learning capability but analysis of a trained network is difficult. On the other hand, extraction of fuzzy rules is difficult but once they have been extracted, it is relatively easy to analyze the fuzzy system. Thi…s book solves the above problems by developing new learning paradigms and architectures for neural networks and fuzzy systems. The book consists of two parts: Pattern Classification and Function Approximation. In the first part, based on the synthesis principle of the neural-network classifier: A new learning paradigm is discussed and classification performance and training time of the new paradigm for several real-world data sets are compared with those of the widely-used back-propagation algorithm; Fuzzy classifiers of different architectures based on fuzzy rules can be defined with hyperbox, polyhedral, or ellipsoidal regions. The book discusses the unified approach for training these fuzz y classifiers; The performance of the newly-developed fuzzy classifiers and the conventional classifiers such as nearest-neighbor classifiers and support vector machines are evaluated using several realworld data sets and their advantages and disadvantages are clarified. In the second part: Function approximation is discussed extending the discussions in the first part; Performance of the function approximators is compared. This book is aimed primarily at researchers and practitioners in the field of artificial intelligence and neural networks. 352 pp. Englisch.
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Da: moluna, Greven, Germaniamoluna
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EUR 92,27
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The unified approach for extracting fuzzy rules against different fuzzy classifier architecturesA new learning paradigm for neural network classifiers based on the network synthesis principleExtensive performance com…parisons including conventional c.
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 150,44
EUR 7,57 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 4 disponibili
Condizione: New. Print on Demand pp. 352 Illus.
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 154,16
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 4 disponibili
Condizione: New. PRINT ON DEMAND pp. 352.
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 106,99
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Neural networks have a learning capability but analysis of a trained network is difficult. On the other hand, extraction of fuzzy rules is difficult but once they have been extracted, it is relatively easy to analyze the fuzzy system. This bo…ok solves the above problems by developing new learning paradigms and architectures for neural networks and fuzzy systems.The book consists of two parts: Pattern Classification and Function Approximation. In the first part, based on the synthesis principle of the neural-network classifier: A new learning paradigm is discussed and classification performance and training time of the new paradigm for several real-world data sets are compared with those of the widely-used back-propagation algorithm; Fuzzy classifiers of different architectures based on fuzzy rules can be defined with hyperbox, polyhedral, or ellipsoidal regions. The book discusses the unified approach for training these fuzzy classifiers; The performance of the newly-developed fuzzy classifiers and the conventional classifiers such as nearest-neighbor classifiers and support vector machines are evaluated using several real-world data sets and their advantages and disadvantages are clarified.In the second part: Function approximation is discussed extending the discussions in the first part; Performance of the function approximators is compared.This book is aimed primarily at researchers and practitioners in the field of artificial intelligence and neural networks.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 352 pp. Englisch.
