Learning of Trapezoid Fuzzy Number Weights in Fuzzy Neural Networks

Learning in Fuzzy Neural Networks

In our fuzzy neural networks fuzzy weights and fuzzy operations are used for training crisp and fuzzy data. Theoretical studies of fuzzy networks where triangular fuzzy numbers are used, show that the output behaviour of these networks can be estimated for arbitrary input data. To make use of these properties we present two learning algorithms for our networks. We implemented and tested them an...

INTEGRATED ADAPTIVE FUZZY CLUSTERING (IAFC) NEURAL NETWORKS USING FUZZY LEARNING RULES

The proposed IAFC neural networks have both stability and plasticity because theyuse a control structure similar to that of the ART-1(Adaptive Resonance Theory) neural network.The unsupervised IAFC neural network is the unsupervised neural network which uses the fuzzyleaky learning rule. This fuzzy leaky learning rule controls the updating amounts by fuzzymembership values. The supervised IAFC ...

Supervised Learning in Fuzzy Neural Networks

Fuzzy Sets, Fuzzy Controllers, and Neural Networks

This paper gives a short introduction into Fuzzy Set Theory, presents an overview on fuzzy controllers, and discusses possible combinations between fuzzy controllers and neural networks. Fuzzy Sets suggested by L.A. Zadeh 32] ooer a possibility to formally describe linguistic expressions like tall, fast, medium, etc., and to operate on them. Fuzzy controllers use fuzzy sets to represent linguis...

Fuzzy Neural Networks

This paper comparator networks a well-known model of parallel computation. This model is used extensively for keys arrangement tasks such as sorting and selection. This work investigates several aspects of comparator networks. It starts with presenting handy tools for analysis of comparator networks in the form of conclusive sets non-binary vectors that verify a specific functionality. The 0-1 ...