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Volumn 22, Issue 7, 2010, Pages 1927-1959

Norm-observable operator models

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL MODEL; LETTER; PROBABILITY; STATISTICAL MODEL;

EID: 77955997233     PISSN: 08997667     EISSN: 1530888X     Source Type: Journal    
DOI: 10.1162/neco.2010.03-09-983     Document Type: Letter
Times cited : (23)

References (22)
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    • Baum, L.E.1    Petrie, T.2    Soules, G.3    Weiss, N.4
  • 2
    • 0000802938 scopus 로고    scopus 로고
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    • Bengio, Y. (1999). Markovian models for sequential data. Neural Computing Surveys, 2, 129-162.
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    • Bengio, Y.1
  • 3
    • 55049095024 scopus 로고    scopus 로고
    • Hidden Markov models and other finite state automata for sequence processing
    • M. A., Arbin (Ed.), Cambridge, MA: MIT Press
    • Bourlard, H., & Bengio, S. (2002). Hidden Markov models and other finite state automata for sequence processing. In M. A., Arbin (Ed.), The handbook of brain theory and neural networks. Cambridge, MA: MIT Press.
    • (2002) The handbook of brain theory and neural networks
    • Bourlard, H.1    Bengio, S.2
  • 4
    • 0018011435 scopus 로고
    • Kronecker product and matrix calculus in system theory
    • Brewer, J. W. (1978). Kronecker product and matrix calculus in system theory. IEEE Transactions on Circuits and Systems, CAS-25(9), 772-781.
    • (1978) IEEE Transactions on Circuits and Systems , vol.CAS-25 , Issue.9 , pp. 772-781
    • Brewer, J.W.1
  • 10
    • 34447302314 scopus 로고    scopus 로고
    • Asymptotic mean stationarity of sources with finite evolution dimension
    • Faigle, U., & Schönhuth, A. (2007). Asymptotic mean stationarity of sources with finite evolution dimension. IEEE Transactions on Information Theory, 53, 2342-2348.
    • (2007) IEEE Transactions on Information Theory , vol.53 , pp. 2342-2348
    • Faigle, U.1    Schönhuth, A.2
  • 11
    • 0000582955 scopus 로고
    • On stochastic processes derived from Markov chains
    • Heller, A. (1965). On stochastic processes derived from Markov chains. Annals of Mathematical Statistics, 36, 1286-1291.
    • (1965) Annals of Mathematical Statistics , vol.36 , pp. 1286-1291
    • Heller, A.1
  • 13
    • 0026837871 scopus 로고
    • Identifiability of hidden Markov in-formation sources and their minimum degrees of freedom
    • Ito, H., Amari, S.-I., & Kobayashi, K. (1992). Identifiability of hidden Markov in-formation sources and their minimum degrees of freedom. IEEE Trans. Inform. Theory, 38(2), 324-333.
    • (1992) IEEE Trans. Inform. Theory , vol.38 , Issue.2 , pp. 324-333
    • Ito, H.1    Amari, S.-I.2    Kobayashi, K.3
  • 16
    • 0034198996 scopus 로고    scopus 로고
    • Observable operator models for discrete stochastic time series
    • Jaeger, H. (2000). Observable operator models for discrete stochastic time series. Neural Computation, 12(6), 1371-1398.
    • (2000) Neural Computation , vol.12 , Issue.6 , pp. 1371-1398
    • Jaeger, H.1
  • 18
    • 1942449765 scopus 로고    scopus 로고
    • Predictive representation of state
    • T. G. Deterrich, S. Becker, & Z. Ghahramani (Eds.), Cambridge, MA: MIT Press
    • Littman, M. L., Sutton, R. S., & Satinder, S. (2001). Predictive representation of state. In T. G. Deterrich, S. Becker, & Z. Ghahramani (Eds.), Advances in neural information processing systems, 14 (pp. 1555-1561), Cambridge, MA: MIT Press.
    • (2001) Advances in neural information processing systems , vol.14 , pp. 1555-1561
    • Littman, M.L.1    Sutton, R.S.2    Satinder, S.3
  • 19
    • 0024610919 scopus 로고
    • A tutorial on hidden Markov models and selected applications in speech recognition
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    • Rabiner, L.R.1
  • 22
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    • A bound on modeling error in observable operator models and an associated learning algorithm
    • Zhao, M.-J., Jaeger, H., & Thon, M. (2009). A bound on modeling error in observable operator models and an associated learning algorithm. Neural Computation, 20(9), 2687-2712.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.