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

Pages: 391 - 398, Issue Special, September 2007

 Abstract        Full Text (184.3K)              

Xilin Fu - School of Mathematical Science, Shandong Normal University, Jinan, Shandong 250014, P.R., China (email)
Zhang Chen - School of Mathematics and System Sciences, Shandong University, Jinan, Shandong, 250100, P. R., China (email)

Abstract: 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:  Discrete neural networks, coincidence degree, periodic solution, time delay, global exponential stability.
Mathematics Subject Classification:  39A10, 39A11.

Received: September 2006;      Revised: June 2007;      Published: September 2007.