DocumentCode :
304038
Title :
Implementing fuzzy logic control with a biologically plausible neural net
Author :
Alexander, John R., Jr.
Author_Institution :
Towson State Univ., MD, USA
Volume :
2
fYear :
1996
fDate :
8-11 Sep 1996
Firstpage :
886
Abstract :
Abeles (1982) and Alkon et al. (1989) stressed the fact that neurons possess an average firing rate, and may fire both above or below this average. The equations developed by the author (1991) (called the RX equations) include an average firing rate. The RX equations have been shown to be useful in solving elementary control problems. In fact, control, on a par with a fuzzy logic controller, may be achieved by a network of as few as three neurons, two input and one output-a three-neuron controller (TNC). In this paper we discuss the analogies between fuzzy logic control and control exercised by a TNC and the restrictions existing in application of the TNC technique
Keywords :
fuzzy control; neurocontrollers; RX equations; average firing rate; biologically plausible neural net; fuzzy logic control; three-neuron controller; Biological control systems; Control systems; Differential equations; Fuzzy logic; Input variables; Mathematics; Neural networks; Neurons; Nonlinear equations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-7803-3645-3
Type :
conf
DOI :
10.1109/FUZZY.1996.552296
Filename :
552296
Link To Document :
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