integrated adaptive fuzzy clustering (iafc) neural networks using fuzzy learning rules

نویسندگان

yong soo kim

z. zenn bien

چکیده

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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عنوان ژورنال:
iranian journal of fuzzy systems

ناشر: university of sistan and baluchestan

ISSN 1735-0654

دوره 2

شماره 2 2005

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