Adaptive Finite-Time Complete Periodic Synchronization of Memristive Neural Networks with Time Delays
Adaptive Finite-Time Complete Periodic Synchronization of Memristive Neural Networks with Time Delays
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DOI：
10.1007/s11063-014-9373-6
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发表时间：
2015-12
影响因子：
3.1
通讯作者：
Huaiqin Wu;Ruoxia Li;Xiaowei Zhang;Rong Yao
中科院分区：
文献类型：
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作者：
Huaiqin Wu;Ruoxia Li;Xiaowei Zhang;Rong Yao
研究了时滞记忆神经网络的自适应有限时间完全周期同步问题。在右手边不连续微分方程Filippov解的框架下，基于集值分析理论中的Mawhin-like重合定理，证明了周期解的存在性。采用Lyapunov-Krasovskii泛函方法设计自适应控制器，利用自适应更新规律确定未知控制参数。利用线性矩阵不等式给出了一种新的有限时间完全同步条件，保证了同步目标的实现。最后通过算例验证了理论结果的有效性。
This paper is concerned with the adaptive finite-time complete periodic synchronization issue for memristive based neural networks with time delays. Under the framework of Filippov solutions of the differential equations with discontinuous right-hand side, based on Mawhin-like coincidence theorem in set-valued analysis theory, the existence of periodic solution is proved. By applying Lyapunov–Krasovskii functional approach, adaptive controller is designed and unknown control parameters are determined by adaptive update law. A novel and useful finite-time complete synchronization condition is obtained in terms of linear matrix inequalities to ensure the synchronization goal. An illustrative example is given to demonstrate the effectiveness of the theoretical results.