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Robustness of Fuzzy Flip-Flop Based Neural Network

TitleRobustness of Fuzzy Flip-Flop Based Neural Network
Publication TypeConference Paper
Year of Publication2010
Publication LanguageEnglish
Pagination207-211
AuthorsLovassy, R., L. T. Kóczy, and L. Gál
Conference Name11th IEEE International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI
Date Published2010
Conference LocationBudapest, Hungary
ISBN Number978-1-4244-9278-7
Abstract

In this paper the robustness of three different types of Fuzzy Flip-Flop based Neural Network (FNN) and the standard tansig based neural networks is compared from the various test function approximation goodness points of view. It is tested how well the fuzzy flip-flop based and the simulated neural networks handle the test data sets outlier points. The robust design of the FNN is presented, and the best suitable fuzzy neuron type is emphasized. Furthermore, the sensitivity of fuzzy neural networks to the fuzzy neuron type and hidden layers neuron number is evaluated.
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