메뉴 건너뛰기




Volumn 32, Issue 4, 2007, Pages 1491-1498

Particle-filter-based estimation and prediction of chaotic states

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CHAOS THEORY; COMPUTER SIMULATION; TIME SERIES ANALYSIS;

EID: 33845414526     PISSN: 09600779     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.chaos.2005.11.098     Document Type: Article
Times cited : (26)

References (16)
  • 2
    • 21944433022 scopus 로고    scopus 로고
    • Controlling chaos using input-output linearization approach
    • Yu X. Controlling chaos using input-output linearization approach. Int J Bifurcat Chaos 7 (1997) 1659-1664
    • (1997) Int J Bifurcat Chaos , vol.7 , pp. 1659-1664
    • Yu, X.1
  • 3
    • 13844256532 scopus 로고    scopus 로고
    • Controlling uncertain Van der Pol oscillator via robust nonlinear feedback control
    • Chen M.Y., Han Z.Z., Shang Y., et al. Controlling uncertain Van der Pol oscillator via robust nonlinear feedback control. Int J Bifurcat Chaos 14 (2004) 1671-1681
    • (2004) Int J Bifurcat Chaos , vol.14 , pp. 1671-1681
    • Chen, M.Y.1    Han, Z.Z.2    Shang, Y.3
  • 5
    • 0343689904 scopus 로고
    • Synchronization in chaotic systems
    • Pecora L.M., and Carroll T.L. Synchronization in chaotic systems. Phys Rev Lett 64 (1990) 821-824
    • (1990) Phys Rev Lett , vol.64 , pp. 821-824
    • Pecora, L.M.1    Carroll, T.L.2
  • 6
    • 0041988793 scopus 로고
    • A unified framework for synchronization an control of dynamical systems
    • Wu C.W., and Chua L.O. A unified framework for synchronization an control of dynamical systems. Int J Bifurcat Chaos 4 (1994) 979-998
    • (1994) Int J Bifurcat Chaos , vol.4 , pp. 979-998
    • Wu, C.W.1    Chua, L.O.2
  • 7
    • 0038396297 scopus 로고    scopus 로고
    • Chaotic-time-series reconstruction by the Bayesian paradigm: right results by wrong methods
    • Kevin J. Chaotic-time-series reconstruction by the Bayesian paradigm: right results by wrong methods. Phys Rev E 67 (2003) 026212
    • (2003) Phys Rev E , vol.67 , pp. 026212
    • Kevin, J.1
  • 8
    • 37649032574 scopus 로고    scopus 로고
    • Learning and predicting time series by neural networks
    • Ansgar F., Wolfgang K., and Ido K. Learning and predicting time series by neural networks. Phys Rev E 65 (2002) 050903
    • (2002) Phys Rev E , vol.65 , pp. 050903
    • Ansgar, F.1    Wolfgang, K.2    Ido, K.3
  • 9
    • 0027580559 scopus 로고
    • Novel approach to nonlinear/non-Gaussian Bayesian state estimation
    • Gordon N.J., Salmond D.J., and Smith A.F.M. Novel approach to nonlinear/non-Gaussian Bayesian state estimation. IEE Proc-F 140 (1993) 107-113
    • (1993) IEE Proc-F , vol.140 , pp. 107-113
    • Gordon, N.J.1    Salmond, D.J.2    Smith, A.F.M.3
  • 10
    • 1542427941 scopus 로고    scopus 로고
    • Filtering via simulation: auxiliary particle filters
    • Pitt M., and Shephard N. Filtering via simulation: auxiliary particle filters. J Am Statist Assoc 94 (1999) 590-599
    • (1999) J Am Statist Assoc , vol.94 , pp. 590-599
    • Pitt, M.1    Shephard, N.2
  • 11
    • 0003345004 scopus 로고    scopus 로고
    • Improving regularised particle filters
    • Doucet A., de Freitas J.F.G., and Gordon N.J. (Eds), Springer-Verlag, New York
    • Musso C., Oudjane N., and LeGland F. Improving regularised particle filters. In: Doucet A., de Freitas J.F.G., and Gordon N.J. (Eds). Sequential Monte Carlo methods in practice (2001), Springer-Verlag, New York
    • (2001) Sequential Monte Carlo methods in practice
    • Musso, C.1    Oudjane, N.2    LeGland, F.3
  • 12
    • 0036475447 scopus 로고    scopus 로고
    • A tutorial on particle filters for on-line nonlinear non-Gaussian Bayesian tracking
    • Arulampalam M.S., Maskell S., Gordon N., et al. A tutorial on particle filters for on-line nonlinear non-Gaussian Bayesian tracking. IEEE Trans Signal Process 50 (2001) 174-188
    • (2001) IEEE Trans Signal Process , vol.50 , pp. 174-188
    • Arulampalam, M.S.1    Maskell, S.2    Gordon, N.3
  • 13
    • 0036508204 scopus 로고    scopus 로고
    • Particle methods for Bayesian modelling and enhancement of speech signals
    • Vermaak J., Andrieu C., Doucet A., et al. Particle methods for Bayesian modelling and enhancement of speech signals. IEEE Trans Speech Audio Process 10 (2002) 173-185
    • (2002) IEEE Trans Speech Audio Process , vol.10 , pp. 173-185
    • Vermaak, J.1    Andrieu, C.2    Doucet, A.3
  • 14
    • 0035435254 scopus 로고    scopus 로고
    • Particle filtering based likelihood ratio approach to fault diagnosis in nonlinear stochastic systems
    • Li P., and Kadirkamanathan V. Particle filtering based likelihood ratio approach to fault diagnosis in nonlinear stochastic systems. IEEE Trans Syst Man Cybern Part C-Appl Rev 31 (2001) 337-343
    • (2001) IEEE Trans Syst Man Cybern Part C-Appl Rev , vol.31 , pp. 337-343
    • Li, P.1    Kadirkamanathan, V.2
  • 15
    • 85126433206 scopus 로고    scopus 로고
    • Zhang B, Chen M, Zhou D. Chaotic secure communication based on particle filtering. Chaos, Solitons & Fractals, in press, doi:10.1016/j.chaos.2005.09.019.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.