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Volumn , Issue , 2007, Pages 427-432

A supervised learning approach based on STDP and polychronization in spiking neuron networks

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL CAPABILITY; NETWORK MODELING; NETWORK PROCESSING; OUTPUT NEURONS; POLYCHRONIZATION; SPIKING NEURON NETWORKS; SUPERVISED LEARNING APPROACHES; SYNAPTIC DELAYS;

EID: 84886993112     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (5)

References (9)
  • 1
    • 33644898137 scopus 로고    scopus 로고
    • Polychronization: Computation with spikes
    • E.M. Izhikevich. Polychronization: Computation with spikes. Neural Computation, 18(1):245-282, 2006.
    • (2006) Neural Computation , vol.18 , Issue.1 , pp. 245-282
    • Izhikevich, E.M.1
  • 2
    • 0033667165 scopus 로고    scopus 로고
    • Synaptic plasticity: Taming the beast
    • L.F. Abbott and S.B. Nelson. Synaptic plasticity: taming the beast. Nature Neuroscience, 3:1178-1183, 2000.
    • (2000) Nature Neuroscience , vol.3 , pp. 1178-1183
    • Abbott, L.F.1    Nelson, S.B.2
  • 3
    • 78349289898 scopus 로고    scopus 로고
    • Adaptive nonlinear system identification with Echo State Networks
    • In S. Becker, S. Thrun, and K. Obermayer, editors, NIPS*2002, MIT Press
    • H. Jaeger. Adaptive nonlinear system identification with Echo State Networks. In S. Becker, S. Thrun, and K. Obermayer, editors, NIPS*2002, Advances in Neural Information Processing Systems, volume 15, pages 593-600. MIT Press, 2003.
    • (2003) Advances In Neural Information Processing Systems , vol.15 , pp. 593-600
    • Jaeger, H.1
  • 4
    • 0036834701 scopus 로고    scopus 로고
    • Real-time computing without stable states: A new framework for neural computation based on perturbations
    • W. Maass, T. Natschläger, and H. Markram. Real-time computing without stable states: A new framework for neural computation based on perturbations. Neural Computation, 14(11):2531-2560, 2002.
    • (2002) Neural Computation , vol.14 , Issue.11 , pp. 2531-2560
    • Maass, W.1    Natschläger, T.2    Markram, H.3
  • 7
    • 33750114071 scopus 로고    scopus 로고
    • Evolutionary supervision of a dynamical neural network allows learning with on-going weights
    • IEEE-INNS
    • D. Meunier and H. Paugam-Moisy. Evolutionary supervision of a dynamical neural network allows learning with on-going weights. In IJCNN'2005, Int. Joint Conf. on Neural Networks, pages 1493-1498. IEEE-INNS, 2005.
    • (2005) IJCNN'2005, Int. Joint Conf. On Neural Networks , pp. 1493-1498
    • Meunier, D.1    Paugam-Moisy, H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.