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Volumn 2, Issue , 2002, Pages 1820-1825

System identification via a computational Bayesian approach

Author keywords

[No Author keywords available]

Indexed keywords

ASYMPTOTIC STABILITY; ERRORS; FREQUENCY RESPONSE; MARKOV PROCESSES; MAXIMUM LIKELIHOOD ESTIMATION; STATISTICAL METHODS;

EID: 0036994435     PISSN: 01912216     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (3)

References (11)
  • 2
    • 0033740817 scopus 로고    scopus 로고
    • Stochastic sampling algorithms for state estimation of jump Markov linear systems
    • A. Doucet, A. Logothetis, and V. Krishnamurthy, Stochastic sampling algorithms for state estimation of jump Markov linear systems, IEEE Trans. Automat. Control, 45 (2000), pp. 188-202.
    • (2000) IEEE Trans. Automat. Control , vol.45 , pp. 188-202
    • Doucet, A.1    Logothetis, A.2    Krishnamurthy, V.3
  • 4
    • 84874286884 scopus 로고
    • Monte Carlo techniques to estimate the conditional expectation in multi-stage non-linear filtering
    • J. E. Handschin and D. Q. Mayne, Monte Carlo techniques to estimate the conditional expectation in multi-stage non-linear filtering, Internat. J. Control (1), 9 (1969), pp. 547-559.
    • (1969) Internat. J. Control , vol.9 , Issue.1 , pp. 547-559
    • Handschin, J.E.1    Mayne, D.Q.2
  • 6
    • 77956890234 scopus 로고
    • Monte Carlo sampling methods using markov chains and their applications
    • W. Hastings, Monte Carlo sampling methods using markov chains and their applications, Biometrika, 57 (1970), pp. 97-109.
    • (1970) Biometrika , vol.57 , pp. 97-109
    • Hastings, W.1
  • 7
    • 0032359151 scopus 로고    scopus 로고
    • Sequential Monte Carlo methods for dynamic systems
    • J. S. Liu and R. Chen, Sequential Monte Carlo methods for dynamic systems. J. Amer. Statist. Assoc., 93 (1998), pp. 1032-1044.
    • (1998) J. Amer. Statist. Assoc. , vol.93 , pp. 1032-1044
    • Liu, J.S.1    Chen, R.2
  • 10
    • 0013254581 scopus 로고    scopus 로고
    • System identification via a computational Bayesian approach
    • tech. rep., School of Elec. Eng, Univ. Newc.
    • B. Ninness and S. Henriksen, System identification via a computational Bayesian approach, tech. rep., School of Elec. Eng, Univ. Newc., 2002.
    • (2002)
    • Ninness, B.1    Henriksen, S.2
  • 11
    • 0000576595 scopus 로고
    • Markov chains for exploring posterior distributions
    • With discussion and a rejoinder by the author
    • L. Tierney, Markov chains for exploring posterior distributions, Ann. Statist., 22 (1994), pp. 1701-1762. With discussion and a rejoinder by the author.
    • (1994) Ann. Statist. , vol.22 , pp. 1701-1762
    • Tierney, L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.