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Könyv Pattern Classification Shigeo Abe

Pattern Classification

Neuro-fuzzy Methods and Their Comparison

Szerző: Shigeo Abe
Nyelv: Angol
Kötés: Kemény kötésű
Kiadó: Springer London Ltd
Elérhetőség: Beszállítói készleten
Küldés 10-13 napon belül
38 435 Ft
Neural networks have a learning capability but analysis of a trained network is difficult. On the ot...

Információk a könyvről

Szerző
Shigeo Abe
Nyelv
Angol
Kötés
Könyv - Kemény kötésű
Kiadva
2000
oldal
327
EAN
9781852333522
ISBN
1852333529
Enbook ID
01435210
Kiadó
Springer London Ltd
Súly
1480
Méretek
155 x 235 x 23

Teljes leírás

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 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.

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