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Volumn 32, Issue 6, 1999, Pages 483-502

Dynamic models for nonstationary signal segmentation

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; CLUSTER ANALYSIS; ELECTROENCEPHALOGRAM; HUMAN; PRIORITY JOURNAL; SIGNAL NOISE RATIO; SIGNAL PROCESSING; SIMULATION; STATISTICAL MODEL;

EID: 0033395078     PISSN: 00104809     EISSN: None     Source Type: Journal    
DOI: 10.1006/cbmr.1999.1511     Document Type: Article
Times cited : (52)

References (16)
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    • Pardey, J.1    Roberts, S.2    Tarassenko, L.3
  • 2
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    • Estimation of running frequency spectra using a Kalman filter algorithm
    • Skagen W. D. Estimation of running frequency spectra using a Kalman filter algorithm. J. Biomed. Eng. 10:May 1988;275.
    • (1988) J. Biomed. Eng. , vol.10 , pp. 275
    • Skagen, W.D.1
  • 3
    • 0024610919 scopus 로고
    • A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition
    • Rabiner R. L. A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition. Proc. IEEE. 77:1989;257.
    • (1989) Proc. IEEE , vol.77 , pp. 257
    • Rabiner, R.L.1
  • 4
    • 0014537240 scopus 로고
    • Adaptive filtering
    • Jazwinski H. A. Adaptive filtering. Automatica. 5:1969;475.
    • (1969) Automatica , vol.5 , pp. 475
    • Jazwinski, H.A.1
  • 5
    • 0342595197 scopus 로고    scopus 로고
    • Hierarchical Bayesian-Kalman Models for Regularisation and ARD in Sequential Learning
    • DeFreitas J. F. G., Niranjan M., Gee A. H. Hierarchical Bayesian-Kalman Models for Regularisation and ARD in Sequential Learning. Technical Report. 1998.
    • (1998) Technical Report
    • Defreitas, J.F.G.1    Niranjan, M.2    Gee, A.H.3
  • 6
    • 0001396562 scopus 로고
    • Forecasting probability densities by using hidden Markov models with mixed states
    • A. S. Weigend, Gershenfeld N. A. Reading: Addison-Wesley
    • Fraser A. M., Dimitriadis A. Forecasting probability densities by using hidden Markov models with mixed states. Weigend A. S., Gershenfeld N. A. Time Series Prediction: Forecasting the Future and Understanding the Past. 1994;265-282 Addison-Wesley, Reading.
    • (1994) Time Series Prediction: Forecasting the Future and Understanding the Past , pp. 265-282
    • Fraser, A.M.1    Dimitriadis, A.2
  • 8
    • 0343900903 scopus 로고    scopus 로고
    • Dynamic Linear Models, Recursive Least Squares and Steepest Descent Learning
    • Penny W. D., Roberts S. J. Dynamic Linear Models, Recursive Least Squares and Steepest Descent Learning. Technical Report. 1998.
    • (1998) Technical Report
    • Penny, W.D.1    Roberts, S.J.2
  • 12
    • 85031639102 scopus 로고    scopus 로고
    • Temporal and spatial complexity measures for EEG-based brain-computer interfacing
    • in press
    • Roberts, S. J, Penny, W, and, Rezek, I. Temporal and spatial complexity measures for EEG-based brain-computer interfacing, Med. Biol. Eng. Comput, in press.
    • Med. Biol. Eng. Comput
    • Roberts, S.J.1    Penny, W.2    Rezek, I.3
  • 14
    • 0001025418 scopus 로고
    • Bayesian interpolation
    • Mackay D. J. C. Bayesian interpolation. Neural Comput. 4:1992;415.
    • (1992) Neural Comput. , vol.4 , pp. 415
    • Mackay, D.J.C.1
  • 16
    • 84963455448 scopus 로고
    • Estimating the order of hidden Markov models
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    • (1995) Statistics , vol.26 , pp. 345
    • Ryden, T.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.