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Keywords

Fuzzy Logic
linear associative Memory
Recurrent Neural Network
Hopfield Network
Corruption
Bipolar Transmission

Abstract

ABSTRACT This paper studies the utilization of fuzzy logic on pattern recognition sender after analyzing unknown pattern converged from associative. In order to specify the original patterns stored in memory. Results indicated that the addition of fuzzy stage to Hopfielf net to identify the unknown pattern called (FRS) was succeeded in differentiating and identifying unknown patterns were produced by “Hopfield neural network associative memory “(HNMAR) despite of the increasing in signal corruption to relatively high levels. It was demonstrated the possibility of rising the level of performance of memory type “Hopfield” where the signal corruption is at relatively higher percentage.
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