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Volumn , Issue , 2008, Pages 3204-3209

Band-pass reservoir computing

Author keywords

[No Author keywords available]

Indexed keywords

FREQUENCY BANDS; SIGNAL PROCESSING; WAVE FILTERS;

EID: 56349107019     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2008.4634252     Document Type: Conference Paper
Times cited : (26)

References (17)
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    • Jaeger, H.1
  • 2
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    • Real-time computing without stable states: A new framework for neural computation based on perturbations
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    • (2002) Neural Computation , vol.14 , Issue.11 , pp. 2531-2560
    • Maass, W.1    Natschläger, T.2    Markram, H.3
  • 3
    • 34249815487 scopus 로고    scopus 로고
    • An experimental unification, of reservoir computing methods
    • D. Verstraeten, B. Schrauwen, M. D'Haene, and D. Stroobandt, "An experimental unification, of reservoir computing methods," Neural Networks, vol. 20, pp. 391-403, 2007.
    • (2007) Neural Networks , vol.20 , pp. 391-403
    • Verstraeten, D.1    Schrauwen, B.2    D'Haene, M.3    Stroobandt, D.4
  • 5
    • 34249867443 scopus 로고    scopus 로고
    • M. D. Skowronski and J. G. Harris, 2007 Special Issue: Automatic speech recognition using a predictive echo state network classifier. Neural Networks, 20, no. 3, pp. 414-423, 2007.
    • M. D. Skowronski and J. G. Harris, "2007 Special Issue: Automatic speech recognition using a predictive echo state network classifier." Neural Networks, vol. 20, no. 3, pp. 414-423, 2007.
  • 9
    • 34249938474 scopus 로고    scopus 로고
    • Optimization and applications of echo state networks with leaky integrator neurons
    • H. Jaeger, M. Lukosevicius, D. Popovici, and U. Siewert, "Optimization and applications of echo state networks with leaky integrator neurons," Neural Networks, vol. 20, pp. 335-352, 2007.
    • (2007) Neural Networks , vol.20 , pp. 335-352
    • Jaeger, H.1    Lukosevicius, M.2    Popovici, D.3    Siewert, U.4
  • 10
    • 33846023013 scopus 로고    scopus 로고
    • Analysis and design of echo state networks
    • M. C. Ozturk, D. Xu, and J. C. Principe, "Analysis and design of echo state networks," Neural Computation, vol. 19, pp. 111-138, 2006.
    • (2006) Neural Computation , vol.19 , pp. 111-138
    • Ozturk, M.C.1    Xu, D.2    Principe, J.C.3
  • 11
    • 56349112690 scopus 로고    scopus 로고
    • Echo-state networks with band-pass neurons: Towards generic time-scale-independent reservoir structures,
    • PLANET Intelligent Systems GmbH
    • U. Siewert and W. Wustlich, "Echo-state networks with band-pass neurons: Towards generic time-scale-independent reservoir structures," tech. rep., PLANET Intelligent Systems GmbH, 2007.
    • (2007) tech. rep
    • Siewert, U.1    Wustlich, W.2
  • 12
    • 33846543881 scopus 로고    scopus 로고
    • Edge of chaos and prediction of computational performance for neural microcircuit models
    • R. A. Legenstein and W. Maass, "Edge of chaos and prediction of computational performance for neural microcircuit models," Neural Networks, pp. 323-333, 2007.
    • (2007) Neural Networks , pp. 323-333
    • Legenstein, R.A.1    Maass, W.2
  • 14
    • 1842421269 scopus 로고    scopus 로고
    • Harnessing nonlinearity: Predicting chaotic systems and saving energy in wireless telecommunication
    • April 2
    • H. Jaeger and H. Haas, "Harnessing nonlinearity: predicting chaotic systems and saving energy in wireless telecommunication," Science, vol. 308, pp. 78-80, April 2 2004.
    • (2004) Science , vol.308 , pp. 78-80
    • Jaeger, H.1    Haas, H.2
  • 15
    • 3042521956 scopus 로고    scopus 로고
    • Applying lstm to time series predictable through time-window approaches
    • tech. rep, Instituto Dalle Molle di studi sull' intelligenza artificiale
    • F. Gers, D. Eck, and J. Schmidhuber, "Applying lstm to time series predictable through time-window approaches," tech. rep., Instituto Dalle Molle di studi sull' intelligenza artificiale, 2000.
    • (2000)
    • Gers, F.1    Eck, D.2    Schmidhuber, J.3
  • 16
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    • L. Feldkamp, D. Prokhorov, C. Eagen, and F. Yuan, Enhanced multi-stream Kalman filter training for recurrent neural networks. Kluwer, nonlinear modeling: advanced black-box techniques ed., 1998.
    • L. Feldkamp, D. Prokhorov, C. Eagen, and F. Yuan, Enhanced multi-stream Kalman filter training for recurrent neural networks. Kluwer, nonlinear modeling: advanced black-box techniques ed., 1998.
  • 17
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    • Short term memory in echo state networks,
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    • H. Jaeger, "Short term memory in echo state networks," Tech. Rep. GMD Report 152, German National Research Center for Information Technology, 2001.
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    • Jaeger, H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.