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.
fDate :
5/1/2007 12:00:00 AM
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;
Journal_Title :
Circuits and Systems II: Express Briefs, IEEE Transactions on
DOI :
10.1109/TCSII.2007.892399
