Applied Mathematics and Mechanics (English Edition) ›› 2008, Vol. 29 ›› Issue (11): 1427-1438 .doi: https://doi.org/10.1007/s10483-008-1104-x

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Stability analysis of delayed cellular neural networks with and without noise perturbation

ZHANG Xue-juan1, WANG Guan-xiang2 and LIU Hua3   

  1. 1. Department of Mathematics, Shaoxing University,Shaoxing 312000, Zhejiang Province, P. R. China; 2. LMAM, School of Mathematical Sciences,Peking University, Beijing 100871, P. R. China; 3. Guanghua School of Management, Peking University, Beijing 100871, P. R. China
  • Received:2008-04-08 Revised:2008-09-03 Online:2008-11-01 Published:2008-11-01
  • Contact: WANG Guan-xiang

Abstract: The stability of a class of delayed cellular neural networks (DCNN) with or without noise perturbation is studied. After presenting a simple and easily checkable condition for the global exponential stability of a deterministic system, we further investigate the case with noise perturbation. When DCNN is perturbed by external noise, the system is globally stable. An important fact is that, when the system is perturbed by internal noise, it is globally exponentially stable only if the total noise strength is within a certain bound. This is significant since the stochastic resonance phenomena have been found to exist in many nonlinear systems.

Key words: delayed cellular neural networks, global exponential stability, external/internal noise

2010 MSC Number: 

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