Neural Fuzzy Control Systems With Structure And Parameter Learning

Name: Neural Fuzzy Control Systems With Structure And Parameter Learning
Brand: World Scientific Publishing Co Pte Ltd
SKU: 9789810216139
Price: 258.41 PLN
Availability: InStock

Autor: Chin-Teng Lin

Język:

Oprawa: Twarda

Wydawca: World Scientific Publishing Co Pte Ltd

Dostępność: 50 % szansa

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A general neural-network-based connectionist model, called Fuzzy Neural Network (FNN), is proposed i...

Informacje o książce

Autor

Chin-Teng Lin

Język

Angielski

Oprawa

Książka - Twarda

Data wydania

1994

strony

144

EAN

9789810216139

ISBN

9810216130

Enbook ID

05064625

Wydawca

World Scientific Publishing Co Pte Ltd

Waga

318

Pełny opis

A general neural-network-based connectionist model, called Fuzzy Neural Network (FNN), is proposed in this book for the realization of a fuzzy logic control and decision system. The FNN is a feedforward multi-layered network which integrates the basic elements and functions of a traditional fuzzy logic controller into a connectionist structure which has distributed learning abilities. In order to set up this proposed FNN, the author recommends two complementary structure/parameter learning algorithms, a two-phase hybrid learning algorithm and an on-line supervised structure/parameter learning algorithm. Both of the above two learning algorithms require exact supervised training data for learning. In some real-time applications, exact training data may be expensive or even impossible to get. To solve this reinforcement learning problem for real-world applications, a Reinforcement Fuzzy Neural Network (RFNN) is further proposed. Computer simulation examples are presented to illustrate the performance and applicability of the proposed FNN, RFNN and their associated learning algorithms for various applications.

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