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Volumn 17, Issue 3, 1996, Pages 193-230

Combined deterministic and stochastic system identification and realization: DSR - A subspace approach based on observations

Author keywords

State space methods; Stochastic and deterministic systems; Subspace methods; System identification; Time series analysis

Indexed keywords


EID: 0001629699     PISSN: 03327353     EISSN: None     Source Type: Journal    
DOI: 10.4173/mic.1996.3.3     Document Type: Article
Times cited : (49)

References (17)
  • 1
    • 5244362218 scopus 로고
    • Methods for the identification of state space models from input and output measurements
    • Copenhagen, July 4-6
    • DI RUSCIO, D. (1994). Methods for the identification of state space models from input and output measurements. SYSID 94, The 10th IFAC Symposium on System Identification, Copenhagen, July 4-6.
    • (1994) SYSID 94, The 10th IFAC Symposium on System Identification
    • Di Ruscio, D.1
  • 2
    • 84866093034 scopus 로고
    • A method for the identification of state space models from input and output measurements
    • Program commercial available by Fantoft Process AS, Box 306, N-1301 Sandvika
    • DI RUSCIO, D. (1995). A method for the identification of state space models from input and output measurements. Modeling, Identification and Control, vol. 16, no. 3. Program commercial available by Fantoft Process AS, Box 306, N-1301 Sandvika.
    • (1995) Modeling, Identification and Control , vol.16 , Issue.3
    • Di Ruscio, D.1
  • 3
    • 77952333009 scopus 로고
    • A method for identification of combined deterministic and stochastic systems
    • roma, September 5-8
    • DI RUSCIO, D. (1995b). A method for identification of combined deterministic and stochastic systems. Proceedings of the third European Control Conference, ECC95, roma, September 5-8, pp. 429-434.
    • (1995) Proceedings of the Third European Control Conference, ECC95 , pp. 429-434
    • Di Ruscio, D.1
  • 4
    • 0029736018 scopus 로고    scopus 로고
    • Subspace identification for dynamic process analysis and modeling
    • Halifax, Nova Scotia, May 1996
    • DI RUSCIO, D., and HOLMBERG, A. (1996). Subspace identification for dynamic process analysis and modeling. Control Systems 96, Halifax, Nova Scotia, May 1996.
    • (1996) Control Systems 96
    • Di Ruscio, D.1    Holmberg, A.2
  • 6
    • 0020876896 scopus 로고
    • System identification, reduced order filtering and modeling via canonical variate analysis
    • San Francisco, USA
    • LARIMORE, W. E. (1983). System identification, reduced order filtering and modeling via canonical variate analysis. Proc. of the American Control Conference, San Francisco, USA, pp. 445-451.
    • (1983) Proc. of the American Control Conference , pp. 445-451
    • Larimore, W.E.1
  • 7
    • 0025532490 scopus 로고
    • Canonical Variate Analysis in Identification, Filtering and Adaptive Control
    • Honolulu, Hawaii, December 1990
    • LARIMORE, W. E. (1990). Canonical Variate Analysis in Identification, Filtering and Adaptive Control. Proc. of the 29th Conference on Decision and Control, Honolulu, Hawaii, December 1990, pp. 596-604.
    • (1990) Proc. of the 29th Conference on Decision and Control , pp. 596-604
    • Larimore, W.E.1
  • 9
    • 0003274208 scopus 로고
    • Stochastic realization algorithms
    • R. K. Mehra and D. G. Lainiotis (eds), Academic Press
    • FAURRE, P. L. (1976). Stochastic realization algorithms, in R. K. Mehra and D. G. Lainiotis (eds), System Identification: Advances and Case Studies, Academic Press.
    • (1976) System Identification: Advances and Case Studies
    • Faurre, P.L.1
  • 11
    • 0002334592 scopus 로고
    • A new identification and Model Reduction Algorithm via Singular Value Decomposition
    • Pacific Grove, CA, November 1978
    • KUNG, S. Y. (1978). A new identification and Model Reduction Algorithm via Singular Value Decomposition. Conf. on Circuits, Systems and Computers, Pacific Grove, CA, November 1978, pp. 705-714.
    • (1978) Conf. on Circuits, Systems and Computers , pp. 705-714
    • Kung, S.Y.1
  • 12
    • 0019533482 scopus 로고
    • Principal Component Analysis in Linear Systems: Controllability, Observability, and Model Reduction
    • MOORE, B. C. (1981). Principal Component Analysis in Linear Systems: Controllability, Observability, and Model Reduction. IEEE Trans. on Automatic Control, Vol. AC-26, pp. 17-31.
    • (1981) IEEE Trans. on Automatic Control , vol.AC-26 , pp. 17-31
    • Moore, B.C.1
  • 13
    • 0028330583 scopus 로고
    • N4SID: Subspace Algorithms for the Identification of Combined Deterministic Stochastic Systems
    • VAN OVERSCHEE, P., and DE MOOR, B. (1994). N4SID: Subspace Algorithms for the Identification of Combined Deterministic Stochastic Systems. Automatica, vol. 30, no. 1, pp. 75-94.
    • (1994) Automatica , vol.30 , Issue.1 , pp. 75-94
    • Van Overschee, P.1    De Moor, B.2
  • 15
    • 0029517196 scopus 로고    scopus 로고
    • A Unifying Theorem for Three Subspace System Identification Algorithms
    • VAN OVERSCHEE, P., and DE MOOR, B. (1996). A Unifying Theorem for Three Subspace System Identification Algorithms. Automatica, vol. 31, no. 12, pp. 1853-1864.
    • (1996) Automatica , vol.31 , Issue.12 , pp. 1853-1864
    • Van Overschee, P.1    De Moor, B.2
  • 16
    • 0028330582 scopus 로고
    • Identification of the deterministic part of MIMO state space models given on innovations form from input output data
    • VERHAGEN, M. (1994). Identification of the deterministic part of MIMO state space models given on innovations form from input output data. Automatica, vol. 30, no. 1, pp. 61-74.
    • (1994) Automatica , vol.30 , Issue.1 , pp. 61-74
    • Verhagen, M.1
  • 17
    • 0029509295 scopus 로고
    • Subspace-Based Methods for the Identification of Linear Time-invariant Systems
    • VIBERG, M. (1995). Subspace-Based Methods for the Identification of Linear Time-invariant Systems. Automatica, vol. 31, no. 12, pp. 1835-1851.
    • (1995) Automatica , vol.31 , Issue.12 , pp. 1835-1851
    • Viberg, M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.