Fuzzy logic and neural networks
作者： M.M. Gupta
DOI: 10.1109/ICSYSE.1992.236895
关键词: Intelligent control 、 Neuro-fuzzy 、 Fuzzy logic 、 Artificial intelligence 、 Fuzzy associative matrix 、 Computer science 、 Neural modeling fields 、 Types of artificial neural networks 、 Computational intelligence 、 Adaptive neuro fuzzy inference system 、 Theoretical computer science
摘要: Some basic principles of fuzzy neural computing using synaptic and somatic operations are presented. The systems based upon conventional algebraic (confluence) (aggregation) briefly reviewed. A detailed neuronal morphology logic its generalization in the form T-operators provided. For such neurons, learning adaptation algorithm is developed. >
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M.M. Gupta, J. Qi, Theory of T -norms and fuzzy inference methods Fuzzy Sets and Systems. ,vol. 40, pp. 431- 450 ,(1991) , 10.1016/0165-0114(91)90171-L