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Dynamical Behavior of Complex-Valued Hopfield Neural Networks with Discontinuous Activation Functions

机译:具有不连续激活函数的复值Hopfield神经网络的动力学行为

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摘要

This paper presents some theoretical results on dynamical behavior of complex valued neural networks with discontinuous neuron activations. Firstly, we introduce the Filippov differential inclusions to complex-valued differential equations with discontinuous right-hand side and give the definition of Filippov solution for discontinuous complex-valued neural networks. Secondly, by separating complex-valued neural networks into real and imaginary part, we study the existence of equilibria of the neural networks according to Leray-Schauder alternative theorem of set-valued maps. Thirdly, by constructing appropriate Lyapunov function, we derive the sufficient condition to ensure global asymptotic stability of the equilibria and convergence in finite time. Numerical examples are given to show the effectiveness and merits of the obtained results.
机译:本文提出了具有不连续神经元激活的复杂值神经网络动力学行为的一些理论结果。首先,我们将Filippov微分包含引入到具有不连续右手边的复值微分方程中,并给出了不连续复值神经网络的Filippov解的定义。其次,通过将复值神经网络分为实部和虚部,根据集值映射的Leray-Schauder替代定理,研究了神经网络的均衡性。第三,通过构造适当的李雅普诺夫函数,我们得出充分的条件,以确保均衡的全局渐近稳定性和在有限时间内收敛。数值算例表明了所得结果的有效性和优点。

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