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Parameter recognition for complex networks subjected to noise

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  • Jin, Yunguo

Abstract

The paper addresses the parameters recognition for complex networks with time-varying correlation stochastic effects by constructing response networks. Unlike previous parameters recognition of complex networks, the complex networks are subjected to noise. In particular, the correlation coefficients of random effects for the master networks and the slave works are not constants. In this process of successfully identifying unknown parameters of complex networks, a key point is to construct some suitable approximation functions. A numerical simulation example demonstrates the successful identification of unknown parameters of complex networks under time-varying correlation perturbations.

Suggested Citation

  • Jin, Yunguo, 2019. "Parameter recognition for complex networks subjected to noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    • Handle: RePEc:eee:phsmap:v:536:y:2019:i:c:s0378437119304571
    DOI: 10.1016/j.physa.2019.04.091
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    References listed on IDEAS

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