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Volumn 10, Issue 3, 1998, Pages 731-747

Nonlinear Time-Series Prediction with Missing and Noisy Data

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Indexed keywords


EID: 0347600770     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/089976698300017728     Document Type: Article
Times cited : (16)

References (19)
  • 1
    • 0000652102 scopus 로고
    • Some solutions to the missing feature problem in vision
    • S. J. Hanson, J. D. Cowan, & C. L. Giles (Eds.), San Mateo, CA: Morgan Kaufmann
    • Ahmad, S., & Tresp, V. (1993). Some solutions to the missing feature problem in vision. In S. J. Hanson, J. D. Cowan, & C. L. Giles (Eds.), Neural information processing systems, 5 (pp. 393-440). San Mateo, CA: Morgan Kaufmann.
    • (1993) Neural Information Processing Systems , vol.5 , pp. 393-440
    • Ahmad, S.1    Tresp, V.2
  • 7
    • 85024429815 scopus 로고
    • A new approach to linear filtering and prediction problems
    • Kalman, R. E. (1960). A new approach to linear filtering and prediction problems. Trans. ASME J. Basic Eng., 8, 35-45.
    • (1960) Trans. ASME J. Basic Eng. , vol.8 , pp. 35-45
    • Kalman, R.E.1
  • 8
    • 0026267887 scopus 로고
    • Nonlinear adaptive filtering in nonstationary environments
    • Kadirkamanathan, V., & Niranjan, M. (1991). Nonlinear adaptive filtering in nonstationary environments. ICASSP 91.
    • (1991) ICASSP 91
    • Kadirkamanathan, V.1    Niranjan, M.2
  • 11
    • 0004087397 scopus 로고
    • Probabilistic inference using Markov chain Monte Carlo methods
    • Department of Computer Science, University of Toronto
    • Neal, R. M. (1993). Probabilistic inference using Markov chain Monte Carlo methods (Tech. Rep. No. CRG-TR-93-1). Department of Computer Science, University of Toronto.
    • (1993) Tech. Rep. No. CRG-TR-93-1
    • Neal, R.M.1
  • 12
    • 0002245041 scopus 로고
    • Estimation of conditional densities: A comparison of neural network approaches
    • Sorrento
    • Neuneier, R., Hergert, F., Finnoff, W., & Ormoneit, D. (1994). Estimation of conditional densities: A comparison of neural network approaches (pp. 689-692). Proc. of ICANN 94, Sorrento.
    • (1994) Proc. of ICANN 94 , pp. 689-692
    • Neuneier, R.1    Hergert, F.2    Finnoff, W.3    Ormoneit, D.4
  • 14
    • 0028401031 scopus 로고
    • Neurocontrol of nonlinear dynamical systems with Kalman filter trained recurrent networks
    • Puskorius, G. V., & Feldkamp, L. A. (1994). Neurocontrol of nonlinear dynamical systems with Kalman filter trained recurrent networks. IEEE Transactions on Neural Networks, 5(2), 279-297.
    • (1994) IEEE Transactions on Neural Networks , vol.5 , Issue.2 , pp. 279-297
    • Puskorius, G.V.1    Feldkamp, L.A.2
  • 15
    • 84986753417 scopus 로고
    • An approach to time series smoothing and forecasting using the EM algorithm
    • Shumway, R. H., & Stoffer, D. S. (1982). An approach to time series smoothing and forecasting using the EM algorithm. Journal of Time Series Analysis, 3, 253-264.
    • (1982) Journal of Time Series Analysis , vol.3 , pp. 253-264
    • Shumway, R.H.1    Stoffer, D.S.2
  • 16
    • 0000221272 scopus 로고
    • Training multi-layer perceptrons with the extended Kalman algorithm
    • D. S. Touretzky (Ed.), San Mateo, CA: Morgan Kaufman
    • Singhal, S., & Wu, L. (1989). Training multi-layer perceptrons with the extended Kalman algorithm. In D. S. Touretzky (Ed.), Advances in neural information processing systems, 1 (pp. 133-140). San Mateo, CA: Morgan Kaufman.
    • (1989) Advances in Neural Information Processing Systems , vol.1 , pp. 133-140
    • Singhal, S.1    Wu, L.2
  • 17
    • 0029225970 scopus 로고
    • Missing and noisy data in nonlinear time-series prediction
    • F. Girosi, J. Makhoul, E. Manolakos, & E. Wilson (Eds.), New York: IEEE
    • Tresp, V., & Hofmann, R. (1995). Missing and noisy data in nonlinear time-series prediction. In F. Girosi, J. Makhoul, E. Manolakos, & E. Wilson (Eds.), Neural networks for signal processing 5 (pp. 1-10). New York: IEEE.
    • (1995) Neural Networks for Signal Processing , vol.5 , pp. 1-10
    • Tresp, V.1    Hofmann, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.