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- W2351551188 abstract "The main function of fuzzy perceptron is to discriminate which categories the samples are in by weight learning.An algorithm for a recurrent fuzzy perceptron based on fuzzy logic is presented,and the network structure of the recurrent fuzzy perceptron is similar to traditional perceptron based on addition-production,and the dynamic recursion term is added.Initial weights of network are set to be constant zero,in the case where the dimension of the input vectors is two and the training examples are separable,its finite convergence is proved,i.e.,the training procedure for the network weights will stop in finite steps,and when the dimension is greater than two,stronger conditions are needed to guarantee the finite convergence." @default.
- W2351551188 created "2016-06-24" @default.
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- W2351551188 date "2011-01-01" @default.
- W2351551188 modified "2023-09-24" @default.
- W2351551188 title "Finite convergence for recurrent fuzzy perceptron" @default.
- W2351551188 hasPublicationYear "2011" @default.
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