Title :
Self-evolution fuzzy chaotic neural network and its application
Author :
Tang, Mo ; Bi, Xiaojun ; Wang, Kejun
Author_Institution :
Dept. of Autom., Univ. of Harbin Eng., Harbin, China
Abstract :
In this paper, a novel neural network model called self-evolution fuzzy chaotic neural network is proposed. This model is constructing on the basis of fuzzy Hopfield neural network and self-evolution neural network. Self-evolution neural network has been confirmed of contain chaos characteristic under certain conditions. The new established self-evolution fuzzy chaotic neural network is proved to have both fuzzy clustering function and chaotic associate memory ability throughout theory analysis and simulation.
Keywords :
Hopfield neural nets; fuzzy logic; fuzzy neural nets; chaotic associate memory ability; fuzzy Hopfield neural network; fuzzy clustering function; self-evolution fuzzy chaotic neural network model; Associative memory; Biological neural networks; Chaotic communication; Hopfield neural networks; Neurons; Steady-state; chaos; fuzzy Hopfield neural network; self-evolution fuzzy chaotic neural network; self-evolution neural network;
Conference_Titel :
Mechatronics and Automation (ICMA), 2011 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-8113-2
DOI :
10.1109/ICMA.2011.5985690