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Reconstruction of noise-driven nonlinear networks from node outputs by using high-order correlations
Chen Y(陈阳); Zhang CY(张朝阳); Chen TY(陈天宇); Wang SH(王世红); Hu G(胡岗)
Source PublicationScientific reports
2017
Issue7Pages:44639
Abstract

Many practical systems can be described by dynamic networks, for which modern technique can measure their outputs, and accumulate extremely rich data. Nevertheless, the network structures producing these data are often deeply hidden in the data. The problem of inferring network structures by analyzing the available data, turns to be of great significance. On one hand, networks are often driven by various unknown facts, such as noises. On the other hand, network structures of practical systems are commonly nonlinear, and different nonlinearities can provide rich dynamic features and meaningful functions of realistic networks. Although many works have considered each fact in studying network reconstructions, much less papers have been found to systematically treat both difficulties together. Here we propose to use high-order correlation computations (HOCC) to treat nonlinear dynamics; use two-time correlations to decorrelate effects of network dynamics and noise driving; and use suitable basis and correlator vectors to unifiedly infer all dynamic nonlinearities, topological interaction links and noise statistical structures. All the above theoretical frameworks are constructed in a closed form and numerical simulations fully verify the validity of theoretical predictions.

KeywordComplex Networks
Indexed BySCI
Language英语
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/26154
Collection个人空间
Corresponding AuthorWang SH(王世红); Hu G(胡岗)
Recommended Citation
GB/T 7714
Chen Y,Zhang CY,Chen TY,et al. Reconstruction of noise-driven nonlinear networks from node outputs by using high-order correlations[J]. Scientific reports,2017(7):44639.
APA Chen Y,Zhang CY,Chen TY,Wang SH,&Hu G.(2017).Reconstruction of noise-driven nonlinear networks from node outputs by using high-order correlations.Scientific reports(7),44639.
MLA Chen Y,et al."Reconstruction of noise-driven nonlinear networks from node outputs by using high-order correlations".Scientific reports .7(2017):44639.
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