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Volumn 3070, Issue , 2004, Pages 190-196

Generalized backpropagation through time for continuous time neural networks and discrete time measurements

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; BACKPROPAGATION; DISCRETE TIME CONTROL SYSTEMS; INTEGRATION; LEARNING SYSTEMS; MATHEMATICAL MODELS; PROBLEM SOLVING;

EID: 9444261975     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-24844-6_24     Document Type: Conference Paper
Times cited : (19)

References (14)
  • 1
    • 0028494556 scopus 로고
    • Block partial derivative and its application to neural-net-based direct-model-reference adaptive control
    • Ahmed M. S.: Block partial derivative and its application to neural-net-based direct-model-reference adaptive control, IEE Proc.-Control Theory Appl., vol. 141, pp. 305-314, 1994.
    • (1994) IEE Proc.-Control Theory Appl. , vol.141 , pp. 305-314
    • Ahmed, M.S.1
  • 2
    • 0029183826 scopus 로고
    • Gradient descent learning algorithm overview: A general dynamical systems perspective
    • Baldi P.: Gradient descent learning algorithm overview: A general dynamical systems perspective, IEEE Trans. Neural Networks, vol. 6, pp. 182-195, 1995.
    • (1995) IEEE Trans. Neural Networks , vol.6 , pp. 182-195
    • Baldi, P.1
  • 4
    • 84947479539 scopus 로고    scopus 로고
    • Systems transposed in time and their application to gradient calculation in dynamical systems containing neural nets
    • Zakopane, Poland, May
    • Fujarewicz K.: Systems transposed in time and their application to gradient calculation in dynamical systems containing neural nets, Proc. Fourth Conference Neural Networks and Their Applications, Zakopane, Poland, May 1999.
    • (1999) Proc. Fourth Conference Neural Networks and their Applications
    • Fujarewicz, K.1
  • 5
    • 9444271019 scopus 로고    scopus 로고
    • Identification of heat exchanger using generalized back propagation through time
    • Innsbruck, Austria, February
    • Fujarewicz K.: Identification of heat exchanger using generalized back propagation through time, Proc. Nineteenth IASTED Conference Modelling, Identification and Control, pp. 267-273, Innsbruck, Austria, February 2000.
    • (2000) Proc. Nineteenth IASTED Conference Modelling, Identification and Control , pp. 267-273
    • Fujarewicz, K.1
  • 6
    • 9444245897 scopus 로고    scopus 로고
    • Identification and suboptimal control of heat exchanger using generalized back propagation through time
    • XLVI
    • Fujarewicz K.: Identification and suboptimal control of heat exchanger using generalized back propagation through time, Archives of Control Sciences, vol.10(XLVI), No. 3-4. pp. 167-183.
    • Archives of Control Sciences , vol.10 , Issue.3-4 , pp. 167-183
    • Fujarewicz, K.1
  • 7
    • 9444247013 scopus 로고    scopus 로고
    • Evaluation of a helicopter model using generalized back propagation through
    • L. Rutkowski, J. Kacprzyk (Eds.), Physica-Verlag
    • Fujarewicz K.: Evaluation of a helicopter model using generalized back propagation through, in: L. Rutkowski, J. Kacprzyk (Eds.), Advances in Soft Computing Neural Networks and Soft Computing, Physica-Verlag, 2002.
    • (2002) Advances in Soft Computing Neural Networks and Soft Computing
    • Fujarewicz, K.1
  • 8
    • 9444275465 scopus 로고    scopus 로고
    • On construction of an adjoint system for continuous-discrete systems
    • Istebna, Poland
    • Fujarewicz K.: On construction of an adjoint system for continuous-discrete systems, Proc. of Seminar on Electrical Engineering, pp. 56-61, Istebna, Poland, 2003.
    • (2003) Proc. of Seminar on Electrical Engineering , pp. 56-61
    • Fujarewicz, K.1
  • 9
    • 0003792312 scopus 로고
    • Prentice-Hall, Inc., Engelwood Cliffs, N.J.
    • Kailath T. (1980): Linear Systems, Prentice-Hall, Inc., Engelwood Cliffs, N.J.
    • (1980) Linear Systems
    • Kailath, T.1
  • 10
    • 0026117466 scopus 로고
    • Gradient methods for the optimization of dynamical systems containing neural networks
    • Narendra S. N., Parthasarathy K.: Gradient methods for the optimization of dynamical systems containing neural networks, IEEE Trans. Neural Networks, vol. 2, pp. 252-262, 1991.
    • (1991) IEEE Trans. Neural Networks , vol.2 , pp. 252-262
    • Narendra, S.N.1    Parthasarathy, K.2
  • 11
    • 0029375851 scopus 로고
    • Gradient calculations for dynamic recurrent neural networks: A survey
    • Pearlmutter B. A. (1995): Gradient calculations for dynamic recurrent neural networks: A survey, IEEE Trans. Neural Networks, vol. 6, pp. 1212-1228.
    • (1995) IEEE Trans. Neural Networks , vol.6 , pp. 1212-1228
    • Pearlmutter, B.A.1
  • 12
    • 0001317823 scopus 로고    scopus 로고
    • Diagrammatic derivation of gradient algorithms for neural networks
    • January
    • Wan E., Beaufays F.: Diagrammatic derivation of gradient algorithms for neural networks, Neural Computation, vol. 8, no. 1, January 1996, pp. 182-201.
    • (1996) Neural Computation , vol.8 , Issue.1 , pp. 182-201
    • Wan, E.1    Beaufays, F.2
  • 13
    • 0025503558 scopus 로고
    • Backpropagation through time: What it does and how to do it
    • Werbos P. J. (1990): Backpropagation through time: what it does and how to do it, Proc. IEEE, vol. 78, pp. 1550-1560.
    • (1990) Proc. IEEE , vol.78 , pp. 1550-1560
    • Werbos, P.J.1
  • 14
    • 0001202594 scopus 로고
    • Learning algorithm for continually running fully recurrent neural networks
    • Williams R., Zipser D.: Learning algorithm for continually running fully recurrent neural networks, Neural Computation, vol. 1, pp. 270-280, 1989.
    • (1989) Neural Computation , vol.1 , pp. 270-280
    • Williams, R.1    Zipser, D.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.