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Sinusoidal disturbance induced topology identification of Hindmarsh-Rose neural networks

正弦扰动诱导复杂网络拓扑识别

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Abstract

Topology identification of complex networks is an important problem. Existing research shows that the synchronization of network nodes is an obstacle in the identification of network topology. Identification of the structure of the network presents an interesting challenge during the synchronization of complex networks. We developed a new method using the sinusoidal disturbance to identify the topology when the complex network achieves synchronization. Compared with the disturbance of all the nodes, the disturbance of the key nodes alone can achieve a very good effect. Finally, numerical simulation data are provided to validate our hypothesis.

概要

中文概要

拓扑识别是近年来复杂网络研究的重要问题, 研究表明, 网络上节点同步是拓扑识别过程中的重要障碍. 当节点到达同步时如何进行识别是一个非常有趣的问题. 本文主要研究了节点为Hindmarsh-Rose (HR) 系统的网络结构识别问题, 当网络上HR系统达到同步时, 它们不满足一致激励条件, 拓扑结构不能识别. 此时, 正弦信号扰动能够诱导拓扑识别. 相比于扰动网络上全部节点, 扰动关键节点也能达到拓扑识别的目的.

创新点

拓扑识别问题是复杂网络研究的重要问题, 研究结果表明, 当网络上的节点达到同步时候, 拓扑很难识别. 利用正弦扰动信号, 本文研究了当节点达到同步状态时的拓扑识别问题, 研究表明给节点添加适当的正弦扰动能够诱导出拓扑识别.

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Authors and Affiliations

  1. The School of Mathematics and Statistics, Hunan University of Commerce, Changsha, 410205, China

    Junchan Zhao

  2. Key Laboratory of Hunan Province for Mobile Business Intelligence, Hunan University of Commerce, Changsha, 410205, China

    Junchan Zhao

  3. UNIHAVRE, LMAH, Normandie University, FR-CNRS-3335, ISCN, 76600, Le Havre, France

    M. A. Aziz-Alaoui & Nathalie Corson

  4. UNIHAVRE, LITIS, Normandie University, FR-CNRS-3638, ISCN, 76600, Le Havre, France

    Cyrille Bertelle

Authors
  1. Junchan Zhao
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  2. M. A. Aziz-Alaoui
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  3. Cyrille Bertelle
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  4. Nathalie Corson
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Correspondence to Junchan Zhao.

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Zhao, J., Aziz-Alaoui, M.A., Bertelle, C. et al. Sinusoidal disturbance induced topology identification of Hindmarsh-Rose neural networks. Sci. China Inf. Sci. 59, 112205 (2016). https://doi.org/10.1007/s11432-015-0915-9

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  • DOI: https://doi.org/10.1007/s11432-015-0915-9

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