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Optimal quasi-synchronization of fractional-order memristive neural networks with PSOA

机译:PSOA的分数次数神经网络的最佳准同步

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摘要

In this paper, optimal quasi-synchronization problem for fractional-order memristive delayed neural networks (FMDNNs) is investigated. The model of FMDNNs is transformed into systems with interval parameters. To guarantee quasi-synchronization, a general fractional-order inequalities and aperiodically intermittent controllers are proposed and analyzed. With the help of tools from interval matrix inequalities and fractional stability theory, sufficient conditions are obtained to guarantee quasi-synchronization of the FMDNNs. Synchronization errors about fractional order alpha are clearly stated. The optimal control parameters satisfy the integral square error, and minimal control energy can be computed by using particle swarm optimization algorithm. Finally, simulation examples are given for illustration.
机译:本文研究了分数阶Memristive延迟神经网络(FMDNNS)的最佳准同步问题。 使用间隔参数将FMDNNS模型转换为系统。 为了保证准同步,提出并分析了一般的分数阶不等式和非周期性间歇控制器。 借助于间隔矩阵不等式和分数稳定理论的工具,获得了足够的条件以保证FMDNN的准同步。 关于分数级alpha的同步误差明确说明。 最佳控制参数满足整体方误差,并且可以通过使用粒子群优化算法来计算最小控制能量。 最后,给出了仿真示例的例证。

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