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Quantitative Analysis in Delayed Fractional-Order Neural Networks

机译:延迟分数阶神经网络的定量分析

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This paper mainly investigates the influence of self-connection delay on bifurcation in a fractional neural network. The bifurcation criteria for the proposed systems with self-connection delay or without self-connection delay is figured out using time delay as a bifurcation parameter, respectively. The effects of self-connection delay on bifurcation in a fractional neural network are ascertained in this paper. Comparative analysis indicates that the stability performance of the proposed fractional neural networks is overly undermined by self-connection delay, which cannot be disregarded. In addition, the impact of fractional order on the bifurcation point is revealed. To highlight the proposed original results, two numerical examples are finally presented.
机译:本文主要研究了自连接延迟对分数神经网络分叉分岔的影响。使用时间延迟作为分叉参数分别计算具有自连接延迟或没有自连接延迟的所提出的系统的分叉标准。本文确定了自连接延迟对分数神经网络中分叉分叉的影响。比较分析表明,所提出的分数神经网络的稳定性性能通过自连接延迟过度破坏,即不能忽视。此外,还揭示了分数上的分数令对分叉点的影响。要突出显示所提出的原始结果,最终呈现了两个数值示例。

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