Optimization for nonlinear time series and forecast for sleep

  • Authors:

  • Chenxi Shao;Xiaoxu He;Songtao Tong;Huiling Dou;Ming Yang;Zicai Wang

  • Affiliations:

  • Univ. of Sci. and Techn. of China, China and Control and Simulation Center, Harbin Inst. of Techn., China and MOE, Microsoft Key Lab. of Multimedia Comp. and Comm., Univ. of Sci. and Techn. of Chi ...;Depatment of Computer Science and Technology, University of Science and Technology of China, Hefei, China;Depatment of Computer Science and Technology, University of Science and Technology of China, Hefei, China;Depatment of Computer Science and Technology, University of Science and Technology of China, Hefei, China;Control & Simulation Center, Harbin Institute of Technology, Harbin, China;Control & Simulation Center, Harbin Institute of Technology, Harbin, China

  • Venue:
  • LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part III
  • Year:
  • 2010

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Abstract

It is important processes that phase-space diagram and computation of geometrical eigenvalues are reconstituted in nonlinear dynamical analysis. It's difficult to analyze nonlinear system such as EEG real-time because the algorithms of phase-space diagram reconstitution and geometrical eigenvalue computation are complex on both time and space. The algorithms were optimized to reduce their complexity, after that the algorithms were parallelized, at last the integrated algorithm's running time is 1/30 of the running time before optimization and parallelization. It was found that the value of correlation dimension can reflect sleep stages after analyzing the sleep EEG, final sleep stages were also forecasted simply.