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Volumn , Issue , 2009, Pages 988-996

Replacing supervised classification learning by slow feature analysis in spiking neural networks

Author keywords

[No Author keywords available]

Indexed keywords

DISCRIMINANT ANALYSIS; LEARNING ALGORITHMS; NEURAL NETWORKS; SUPERVISED LEARNING;

EID: 78649884554     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (18)

References (16)
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    • Fisher, R.A.1
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    • Slow feature analysis: A theoretical analysis of optimal free responses
    • L. Wiskott. Slow feature analysis: A theoretical analysis of optimal free responses. Neural Computation, 15(9):2147-2177, 2003.
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    • Wiskott, L.1
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    • Real-time computing without stable states: A new framework for neural computation based on perturbations
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    • Häusler, S.1    Maass, W.2
  • 9
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    • Organizing principles for a diversity of GABAergic interneurons and synapses in the neocortex
    • A. Gupta, Y. Wang, and H. Markram. Organizing principles for a diversity of GABAergic interneurons and synapses in the neocortex. Science, 287:273-278, 2000.
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    • Gupta, A.1    Wang, Y.2    Markram, H.3
  • 10
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    • Synaptic connections and small circuits involving excitatory and inhibitory neurons in layers 2-5 of adult rat and cat neocortex: Triple intracellular recordings and biocytin labelling in vitro
    • A. M. Thomson, D. C. West, Y. Wang, and A. P. Bannister. Synaptic connections and small circuits involving excitatory and inhibitory neurons in layers 2-5 of adult rat and cat neocortex: triple intracellular recordings and biocytin labelling in vitro. Cerebral Cortex, 12(9):936-953, 2002.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.