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Volumn 5768 LNCS, Issue PART 1, 2009, Pages 381-390

Training recurrent neural network using multistream extended kalman filter on multicore processor and cuda enabled graphic processor unit

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL REQUIREMENTS; EXECUTION TIME; GRADIENT BASED ALGORITHM; GRAPHIC PROCESSOR UNITS; MANY-CORE; MODELING ACCURACY; MULTI-CORE PROCESSOR; MULTI-STREAM; TRAINING ALGORITHMS;

EID: 70350605683     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04274-4_40     Document Type: Conference Paper
Times cited : (17)

References (12)
  • 1
    • 0025503558 scopus 로고
    • Backpropagation through time; what it does and how to do it
    • Werbos, P.: Backpropagation through time; what it does and how to do it. Proceedings of the IEEE 78, 1550-1560 (1990)
    • (1990) Proceedings of the IEEE , vol.78 , pp. 1550-1560
    • Werbos, P.1
  • 2
    • 0001202594 scopus 로고
    • A learning algorithm for continually running fully recurrent neural networks
    • Williams, R.J., Zipser, D.: A learning algorithm for continually running fully recurrent neural networks. Neural Computation 1, 270-280 (1989)
    • (1989) Neural Computation , vol.1 , pp. 270-280
    • Williams, R.J.1    Zipser, D.2
  • 3
    • 0013320371 scopus 로고
    • Some observations on the use of the extended Kalman filter as a recurrent network learning algorithm
    • Technical Report NU-CCS-92-1, Northeastern University, College of Computer Science, Boston, MA
    • Williams, R.J.: Some observations on the use of the extended Kalman filter as a recurrent network learning algorithm. Technical Report NU-CCS-92-1, Northeastern University, College of Computer Science, Boston, MA (1992)
    • (1992)
    • Williams, R.J.1
  • 4
    • 0037624007 scopus 로고    scopus 로고
    • Simple recurrent network trained by RTRL and extended Kalman filter algorithms
    • Čerňanský, M., Beňušková, Ľ.: Simple recurrent network trained by RTRL and extended Kalman filter algorithms. Neural Network World 13(3), 223-234 (2003)
    • (2003) Neural Network World , vol.13 , Issue.3 , pp. 223-234
    • Čerňanský, M.1    Beňušková, L.2
  • 5
    • 27544511579 scopus 로고    scopus 로고
    • Recurrent neural network training with the kalman filter-based techniques
    • Trebatický, P.: Recurrent neural network training with the kalman filter-based techniques. Neural network world 15(5), 471-488 (2005)
    • (2005) Neural network world , vol.15 , Issue.5 , pp. 471-488
    • Trebatický, P.1
  • 6
    • 0344592212 scopus 로고    scopus 로고
    • Enhanced multi-stream Kalman filter training for recurrent networks
    • Suykens, J, Vandewalle, J, eds, Kluwer Academic Publishers, Dordrecht
    • Feldkamp, L., Prokhorov, D., Eagen, C., Yuan, F.: Enhanced multi-stream Kalman filter training for recurrent networks. In: Suykens, J., Vandewalle, J. (eds.) Nonlinear Modeling: Advanced Black-Box Techniques, pp. 29-53. Kluwer Academic Publishers, Dordrecht (1998)
    • (1998) Nonlinear Modeling: Advanced Black-Box Techniques , pp. 29-53
    • Feldkamp, L.1    Prokhorov, D.2    Eagen, C.3    Yuan, F.4
  • 7
    • 40649102371 scopus 로고    scopus 로고
    • Toyota prius hev neurocontrol and diagnostics
    • Prokhorov, D.V.: Toyota prius hev neurocontrol and diagnostics. Neural Networks 21, 458-465 (2008)
    • (2008) Neural Networks , vol.21 , pp. 458-465
    • Prokhorov, D.V.1
  • 8
    • 35948991669 scopus 로고    scopus 로고
    • NVIDIA CUDA programming guide
    • NVIDIA:, Technical report
    • NVIDIA: NVIDIA CUDA programming guide. Technical report (2008)
    • (2008)
  • 9
    • 51849166420 scopus 로고    scopus 로고
    • Neural network training with extended kalman filter using graphics processing unit
    • Kůrková, V, Neruda, R, Koutník, J, eds, ICANN 2008, Part II, Springer, Heidelberg
    • Trebatický, P.: Neural network training with extended kalman filter using graphics processing unit. In: Kůrková, V., Neruda, R., Koutník, J. (eds.) ICANN 2008, Part II. LNCS, vol. 5164, pp. 198-207. Springer, Heidelberg (2008)
    • (2008) LNCS , vol.5164 , pp. 198-207
    • Trebatický, P.1
  • 10
    • 70349141071 scopus 로고    scopus 로고
    • Kalman filter training of neural networks: Methodology and applications
    • Budapest, Hungary
    • Prokhorov, D.V.: Kalman filter training of neural networks: Methodology and applications. In: Tutorial on IJCNN 2004, Budapest, Hungary (2004)
    • (2004) Tutorial on IJCNN 2004
    • Prokhorov, D.V.1
  • 11
    • 26444565569 scopus 로고
    • Finding structure in time
    • Elman, J.L.: Finding structure in time. Cognitive Science 14, 179-211 (1990)
    • (1990) Cognitive Science , vol.14 , pp. 179-211
    • Elman, J.L.1
  • 12
    • 0001419757 scopus 로고
    • Distributed representations, simple recurrent networks, and grammatical structure
    • Elman, J.: Distributed representations, simple recurrent networks, and grammatical structure. Machine Learning 7, 195-225 (1991)
    • (1991) Machine Learning , vol.7 , pp. 195-225
    • Elman, J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.