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Existence and Globally Asymptotic Stability of Equilibrium Solution for Fractional-Order Hybrid BAM Neural Networks with Distributed Delays and Impulses

机译:具有分布时滞和脉冲的分数阶混合BAM神经网络平衡解的存在性和全局渐近稳定性

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This paper investigates the existence and globally asymptotic stability of equilibrium solution for Riemann-Liouville fractional-order hybrid BAM neural networks with distributed delays and impulses. The factors of such network systems including the distributed delays, impulsive effects, and two different fractional-order derivatives between the -layer and -layer are taken into account synchronously. Based on the contraction mapping principle, the sufficient conditions are derived to ensure the existence and uniqueness of the equilibrium solution for such network systems. By constructing a novel Lyapunov functional composed of fractional integral and definite integral terms, the globally asymptotic stability criteria of the equilibrium solution are obtained, which are dependent on the order of fractional derivative and network parameters. The advantage of our constructed method is that one may directly calculate integer-order derivative of the Lyapunov functional. A numerical example is also presented to show the validity and feasibility of the theoretical results.
机译:本文研究了具有分布时滞和脉冲的Riemann-Liouville分数阶混合BAM神经网络平衡解的存在性和全局渐近稳定性。同步考虑这样的网络系统的因素,包括分布式时延,脉冲效应以及-层和-层之间的两个不同的分数阶导数。基于收缩映射原理,导出了足够的条件以确保此类网络系统平衡解的存在和唯一性。通过构造由分数积分和定积分项组成的新颖的Lyapunov泛函,获得了平衡解的全局渐近稳定性准则,该准则取决于分数阶导数和网络参数的阶数。我们构造的方法的优点是可以直接计算Lyapunov函数的整数阶导数。数值例子表明了理论结果的有效性和可行性。

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