Title :
Fuzzy logic and neural networks
Author_Institution :
Intelligent Syst. Res. Lab., Saskatchewan Univ., Saskatoon, Sask., Canada
Abstract :
Some basic principles of fuzzy neural computing using synaptic and somatic operations are presented. The neural systems based upon conventional algebraic synaptic (confluence) and somatic (aggregation) operations are briefly reviewed. A detailed neuronal morphology based upon fuzzy logic and its generalization in the form of T-operators are provided. For such fuzzy logic based neurons, the learning and adaptation algorithm is developed
Keywords :
fuzzy logic; learning (artificial intelligence); neural nets; adaptation algorithm; algebraic somatic operations; algebraic synaptic operations; fuzzy logic; fuzzy neural computing; learning; neural networks; neuronal morphology; Biological neural networks; Biology computing; Central nervous system; Fuzzy logic; Fuzzy systems; Intelligent systems; Laboratories; Morphology; Neural networks; Neurons;
Conference_Titel :
Systems Engineering, 1992., IEEE International Conference on
Conference_Location :
Kobe
Print_ISBN :
0-7803-0734-8
DOI :
10.1109/ICSYSE.1992.236895
