Topology estimation of uncertain general complex dynamical networks from noisy time series

Yan Qiu Che, Jiang Wang, Shi Gang Cui, Li Zhao, Bin Deng, Xi Le Wei

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper addresses the problem of simultaneous estimation of the topological structure and unknown parameters of uncertain general complex networks from noisy time series. Usually the complex networks consist of known node models with some unknown parameters and uncertain topological structure. At the same time, only partial states with heavy noise can be observed in real-world complex networks. By means of the unscented Kalman filter (UKF), we estimate the unknown states, parameters as well as topological structure with high accuracy only from partial heavily noise-corrupted states of the nodes. The simulation results verify the effectiveness of the proposed approach.

Original languageEnglish (US)
Title of host publicationProceedings - 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011
Pages1031-1034
Number of pages4
DOIs
StatePublished - Mar 28 2011
Event3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011 - Shanghai, China
Duration: Jan 6 2011Jan 7 2011

Publication series

NameProceedings - 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011
Volume3

Other

Other3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011
CountryChina
CityShanghai
Period1/6/111/7/11

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering

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