Synchronization of state-switching hopfield-type neural networks: A quantized level set approach
Synchronization of state-switching hopfield-type neural networks: A quantized level set approach
复制标题
状态切换hopfield型神经网络的同步:量化水平集方法
DOI:
10.1016/j.chaos.2019.08.016
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发表时间:
2019-12
期刊:
影响因子:
--
通讯作者:
宾红华
中科院分区:
文献类型:
--
作者:
洪雅娴;黄振坤;宾红华
This paper presents the quantized synchronization of state-switching hopfield-type neural networks (SSHNNs) with delays. Due to a quantized controller with saturation, some unified synchronization criterion for SSHNNs with discrete delays and distributed delays are obtained. The quantized adaptive saturation controller (QASC) relies only on the quantized level sets, and hence greatly reduces the control cost and improves the practicability of the SSHNNs synchronization principle. The obtained results are new and improve the existing ones. Finally, numerical examples are given to demonstrate the correctness of our theoretical results.
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影响因子:
7.8
作者:
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通讯作者:
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DOI:
10.1109/tsmc.2017.2732503
发表时间:
2019-02
期刊:
IEEE Transactions on Systems, Man, and Cybernetics: Systems
影响因子:
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DOI:
--
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期刊:
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