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Indexed by:会议论文

Date of Publication:2005-05-30

Included Journals:EI

Volume:3496

Issue:I

Page Number:609-614

Abstract:In this paper, we present a new training algorithm for a fuzzy perceptron. In the case where the dimension of the input vectors is two and the training examples are separable, we can prove a finite convergence, i.e., the training procedure for the network weights will stop after finite steps. When the dimension is greater than two, stronger conditions are needed to guarantee the finite convergence. © Springer-Verlag Berlin Heidelberg 2005.