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SCIENCE CHINA Information Sciences, Volume 59, Issue 11: 112205(2016) https://doi.org/10.1007/s11432-015-0915-9

Sinusoidal disturbance induced topology identification of Hindmarsh-Rose neural networks

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  • ReceivedMar 23, 2016
  • AcceptedMay 6, 2016
  • PublishedOct 14, 2016

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.


Acknowledgment

Acknowledgments

This work was jointly supported by National Natural Science Foundation of China (Grant Nos. 61203159, 61573011, 61273232, 61472136), Haute-Normandie region France, and Project ERDF (European Regional Development Fund) on Complex Networks and Applications.

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