摘要
细胞神经网络已成为应用数学领域研究的热点之一.时滞、反应扩散、不确定项的引入对于广义细胞神经网络的研究具有实际意义.在实际中,需要知道系统在某个固定的时间间隔的动态行为,即系统的有限时间稳定性.在不确定项范数有界的条件下,通过构造Lyapunov泛函,运用Ito公式和稳定性理论,给出了系统的有限时间鲁棒稳定性的充分条件,这些条件既依赖于时滞又依赖于反应扩散项.最后的数值举例表明了结论的有效性.
One of research focuses in applied Mathematics is cellular neural networks. Delay, reaction diffusion, and the uncer- tainties introduced in generalized cellular neural network have real significance. In practice, we need to know the system＇ s dynamic be- havior in fixed time interval, namely the finite-time stability of the system. In the condition of the norm-bounded uncertainties, by con- structing the Lyapunov function, applying the Ito＇ s formula and the theory of stability, the sufficient conditions ensuring the networks to be finite-time robustly stochastically stable are established. These conditions not only depend on the delays but also depend on the reac- tion-diffusion. Finally, a numerical example demonstrates the feasibility of the present conclusions.
出处
《四川师范大学学报（自然科学版）》
CAS
CSCD
北大核心
2014年第2期208-215,共8页
Journal of Sichuan Normal University（Natural Science）
基金
四川省教育厅自然科学青年基金(12ZB040)资助项目
关键词
广义细胞神经网络
有限时间鲁棒稳定性
时滞
反应扩散
随机扰动
generalized cellular neural networks
finite-time robust stability
reaction-diffusion
time delays
stochastic noise
