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

Stability analysis of delayed cellular neural networks with and without noise perturbation
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摘要 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. 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.
出处 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2008年第11期1427-1438,共12页 应用数学和力学(英文版)
基金 the National Natural Science Foundation of China(No.10771155) the Special Foundation for the Authors of National Excellent Doctoral Dissertations of China(FANEDD)
关键词 delayed cellular neural networks global exponential stability external/internal noise delayed cellular neural networks, global exponential stability, external/internal noise
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