Synchronization analysis for static neural networks with hybrid couplings and time delays

Synchronization analysis for static neural networks with hybrid couplings and time delays
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具有混合耦合和时滞的静态神经网络的同步分析

DOI:
10.1016/j.neucom.2013.11.053
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发表时间:
2015-01
期刊:
影响因子:
6
通讯作者:
Wang Junyi
Wang Junyi
中科院分区:
计算机科学2区
文献类型:
--
作者:
Huang Bonan;Zhang Huaguang;Gong Dawei;Wang Junyi

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研究了具有混合耦合的时滞静态神经网络的同步问题。当静态神经网络受到混合耦合的影响时,很难处理这样一个复杂系统中大量高度关联的动态单元。为了解决这个复杂的问题,提出了一种新的方法来处理Kronecker积,使同步问题易于分析。进一步,基于所得结果,利用增广Lyapunov-Krasovskii泛函(LKF)方法,可以处理多个Kronecker乘积项,通过采用具有Kronecker乘积运算的新型增广矩阵,可以引入更宽松的条件.最后,数值例子证明了所提出的同步方案的有效性。
This paper deals with the synchronization problem for delayed static neural networks with hybrid couplings. When the static neural networks are affected by hybrid couplings, it is hard to deal with a large number of highly interconnected dynamical units in such a complex system. In order to solve this complicated problem, a new method is proposed to deal with the Kronecker product, and to make the synchronization problem to be easily analyzed. Further, based on the obtained result, by using the augmented Lyapunov–Krasovskii functional (LKF) method, multitude Kronecker product terms can be handled, which can introduce more relaxed conditions by employing the new type of augmented matrices with the Kronecker product operation. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed synchronization scheme.
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