Lagrangian Stability of Complex-Valued Neural Networks With Distributed Time-Varying Delays
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摘要: 研究了带有变化分布时滞的复值神经网络Lagrange稳定性问题.通过构造合适的LyapunovKrasovskii泛函, 并使用矩阵不等式技巧,建立了网络全局指数Lagrange稳定性的判定条件.提供的判据是复值线性矩阵不等式, 能够使用MATLAB软件的YALMIP工具箱快速计算.
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关键词:
- 复值神经网络 /
- 变化分布时滞 /
- Lagrange稳定性 /
- 复值线性矩阵不等式
Abstract: The Lagrangian stability of complex-valued neural networks with distributed time-varying delays was investigated. By means of the Lyapunov-Krasovskii functional and the matrix inequality techniques, a delay-dependent sufficient condition was obtained to ensure the global exponential stability in a Lagrangian sense for the considered neural networks. The condition is expressed in the form of complex-valued linear matrix inequality, which can be checked numerically with the effective YALMIP toolbox in MATLAB. -
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