DocumentCode
2337641
Title
A novel chaotic neural networks and application
Author
Shi, Wei-Feng ; Xue, Shi-Long
Author_Institution
Dept. of Electri. Autom., Shanghai Maritime Univ., China
Volume
8
fYear
2005
fDate
18-21 Aug. 2005
Firstpage
4651
Abstract
To increase ability of modeling and identification for nonlinear system by neural networks, the characteristics of neurons, learning rule and configuration of networks are researched. The chaotic neuron is introduced to neural networks to form local recurrent chaotic neural networks. The information treatment quantity of the networks is all so increased because there are feed back loops with recurrent networks. The local recurrent chaotic neural networks are used for a marine synchronous generator modeling with a marine real time simulator. In the networks training of generator modeling, a dynamic BP learning algorithm is applied. Compare to other neural networks modeling, the neuron number of hidden layer of the networks is few, the ability of generalization of the chaotic networks system is well.
Keywords
backpropagation; marine engineering; nonlinear systems; power systems; recurrent neural nets; synchronous generators; chaotic neuron; dynamic BP learning algorithm; feed back loops; marine real time simulator; marine synchronous generator modeling; nonlinear system identification; recurrent chaotic neural network; Artificial neural networks; Bifurcation; Cellular neural networks; Chaos; Digital signal processing; Logistics; Neural networks; Neurons; Power system modeling; Recurrent neural networks; BP learning algorithm; Chaotic neural networks; modeling; neuron; recurrent networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location
Guangzhou, China
Print_ISBN
0-7803-9091-1
Type
conf
DOI
10.1109/ICMLC.2005.1527759
Filename
1527759
Link To Document