DocumentCode
841710
Title
Cellular Neural Networks With Transient Chaos
Author
Wang, Lipo ; Liu, Wen ; Shi, Haixiang ; Zurada, Jacek M.
Author_Institution
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ.
Volume
54
Issue
5
fYear
2007
fDate
5/1/2007 12:00:00 AM
Firstpage
440
Lastpage
444
Abstract
A new model of cellular neural networks (CNNs) with transient chaos is proposed by adding negative self-feedbacks into CNNs after transforming the dynamic equation to discrete time via Euler´s method. The simulation on the single neuron model shows stable fix points, bifurcation and chaos. Hence, this new CNN model has richer and more flexible dynamics, and therefore may possess better capabilities of solving various problems, compared to the conventional CNN with only stable dynamics
Keywords
bifurcation; cellular neural nets; chaos; Euler method; bifurcation; cellular neural networks; negative self-feedback; single neuron model; transient chaos; Bifurcation; Cellular neural networks; Chaos; Computational modeling; Hopfield neural networks; Neural networks; Neurons; Power engineering and energy; Simulated annealing; Stochastic processes; Bifurcation; cellular neural networks (CNNs); chaos;
fLanguage
English
Journal_Title
Circuits and Systems II: Express Briefs, IEEE Transactions on
Publisher
ieee
ISSN
1549-7747
Type
jour
DOI
10.1109/TCSII.2007.892399
Filename
4182514
Link To Document