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Boundedness, periodic solutions and global stability for cellular neural networks with variable coefficients and infinite delays

机译:具有可变系数和无限时滞的细胞神经网络的有界性,周期解和全局稳定性

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In this paper, we consider the cellular neural networks with variable coefficients and infinite distributed delays. By introducing the phase space C_g(R_) and applying Lyapunov functional method and Young inequality technique, we first establish a series of criteria on the boundedness, globally asymptotic stability and globally exponential stability. Furthermore, by applying these results and combining the existence theorems of periodic solutions for general functional differential equations with infinite delays, we establish the existence of periodic solutions and its globally asymptotic stability and globally exponential stability for the periodic cellular neural networks with infinite distributed delays. At last, as a special case, we apply these results to the autonomous cellular neural networks with infinite distributed delays and the existence, uniqueness and global stability of equilibrium point are established.
机译:在本文中,我们考虑具有可变系数和无限分布延迟的细胞神经网络。通过引入相空间C_g(R_)并应用Lyapunov函数方法和Young不等式技术,我们首先建立了关于有界性,全局渐近稳定性和全局指数稳定性的一系列标准。此外,通过应用这些结果并结合具有无限时滞的泛函微分方程周期解的存在性定理,我们建立了具有无限分布时滞的周期细胞神经网络的周期解的存在性及其全局渐近稳定性和全局指数稳定性。最后,作为一种特殊情况,我们将这些结果应用于具有无限分布时滞的自主细胞神经网络,并建立了平衡点的存在,唯一性和全局稳定性。

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