Efficient learning algorithm for fuzzy max-product associative memory networks

Ping Xiao; Ying Lin Yu

doi:10.1117/12.271497

4 April 1997 Efficient learning algorithm for fuzzy max-product associative memory networks

Ping Xiao, Ying Lin Yu

Proceedings Volume 3077, Applications and Science of Artificial Neural Networks III; (1997) https://doi.org/10.1117/12.271497
Event: AeroSense '97, 1997, Orlando, FL, United States

Abstract

A kind of fuzzy max-product associative memory network and its learning algorithm are presented in this paper. The connection weight matrix for fuzzy max-product auto- associative memory is determined by the generalized fuzzy solution. Each initial state pattern will be converged another state of the network via the connection weight matrix at one iteration. Fuzzy max-product associative memory network possess strong ability of error-tolerance. The computer simulations show the better performance of the fuzzy max-product associative memory network and its learning algorithm.

Citation Download Citation

Ping Xiao and Ying Lin Yu "Efficient learning algorithm for fuzzy max-product associative memory networks", Proc. SPIE 3077, Applications and Science of Artificial Neural Networks III, (4 April 1997); https://doi.org/10.1117/12.271497

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