Passivity of Fractional-Order Delayed Complex-Valued Neural Networks With Uncertainties
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摘要: 该文研究了一类具有不确定性和时滞的分数阶复值神经网络无源性问题,未将复值神经网络模型拆分成两个实值系统,而是将复值系统当成一个整体直接进行处理.通过构造恰当的Lyapunov函数,并利用矩阵不等式技巧,建立了网络无源性的线性矩阵不等式判据.给出的数值例子和仿真验证了获得结论的可行性和有效性.Abstract: The passivity for a class of fractional-order delayed complex-valued neural networks with uncertainties was studied. The complex-valued neural network was not divided into 2 real-valued neural networks, but treated as a whole. Through construction of the appropriate Lyapunov function and application of the inequality technique, the sufficient criterion in the form of the linear matrix inequality was established to ensure the passivity of the considered neural networks. Numerical examples and simulations verify the feasibility and effectiveness of the obtained conclusion.
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Key words:
- complex-valued neural network /
- fractional-order /
- passivity /
- delay /
- uncertainty
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