American Institute of Mathematical Sciences

Advanced
2007, 2007(Special): 391-398. doi: 10.3934/proc.2007.2007.391

New discrete analogue of neural networks with nonlinear amplification function and its periodic dynamic analysis

Xilin Fu 1, and  Zhang Chen 2,

1. 

School of Mathematical Science, Shandong Normal University, Jinan, Shandong 250014, P.R., China
2. 

School of Mathematics and System Sciences, Shandong University, Jinan, Shandong, 250100, P. R., China

Received  September 2006 Revised  June 2007 Published  September 2007

In this paper, new discrete analogue of a class of neural networks with nonlinear amplification function is obtained by analysis and approximation techniques. Using continuation theorem of coincidence degree theory, periodic solution for discrete model is studied, and sufficient condition is given to guarantee the existence of periodic solution. Moreover, global stability on periodic solution is investigated by Lyapunov method.
Keywords: coincidence degree, global exponential stability., Discrete neural networks, time delay, periodic solution.
Mathematics Subject Classification: 39A10, 39A1.
Citation: Xilin Fu, Zhang Chen. New discrete analogue of neural networks with nonlinear amplification function and its periodic dynamic analysis. Conference Publications, 2007, 2007 (Special) : 391-398. doi: 10.3934/proc.2007.2007.391
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