分数阶复值延迟神经网络中的同步
Synchronization in Fractional-Order Complex-Valued Delayed Neural Networks.
作者信息
Zhang Weiwei, Cao Jinde, Chen Dingyuan, Alsaadi Fuad E
机构信息
School of Mathematics and Computational Science, Anqing Normal University, Anqing 246011, China.
School of Mathematics, Southeast University, Nanjing 210096, China.
出版信息
Entropy (Basel). 2018 Jan 12;20(1):54. doi: 10.3390/e20010054.
This paper discusses the synchronization of fractional order complex valued neural networks (FOCVNN) at the presence of time delay. Synchronization criterions are achieved through the employment of a linear feedback control and comparison theorem of fractional order linear systems with delay. Feasibility and effectiveness of the proposed system are validated through numerical simulations.
本文讨论了分数阶复值神经网络（FOCVNN）在存在时延情况下的同步问题。通过采用线性反馈控制以及分数阶线性时滞系统的比较定理来实现同步准则。所提系统的可行性和有效性通过数值模拟得到验证。
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