integrated adaptive fuzzy clustering (iafc) neural networks using fuzzy learning rules
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abstract
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 neural networks are the supervised neural networkswhich use the fuzzified versions of learning vector quantization (lvq). in this paper,several important adaptive learning algorithms are compared from the viewpoint of structure andlearning rule. the performances of several adaptive learning algorithms are compared usingiris data set.
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Journal title:
iranian journal of fuzzy systemsPublisher: university of sistan and baluchestan
ISSN 1735-0654
volume 2
issue 2 2005
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