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Volumn , Issue , 2011, Pages 1354-1359

Incremental slow feature analysis

Author keywords

[No Author keywords available]

Indexed keywords

AUTONOMOUS LEARNING; ENVIRONMENTAL PROPERTY; INCREMENTAL SLOW FEATURE ANALYSIS; MINOR COMPONENTS; NON-STATIONARY ENVIRONMENT; PRINCIPAL COMPONENTS ANALYSIS; SLOW FEATURE ANALYSIS(SFA); UNDERLYING CAUSE;

EID: 84865105130     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5591/978-1-57735-516-8/IJCAI11-229     Document Type: Conference Paper
Times cited : (20)

References (16)
  • 2
    • 27244444336 scopus 로고    scopus 로고
    • Slow feature analysis yields a rich repertoire of complex cell properties
    • jul
    • Pietro Berkes and Laurenz Wiskott. Slow feature analysis yields a rich repertoire of complex cell properties. Journal of Vision, 5(6):579-602, jul 2005.
    • (2005) Journal of Vision , vol.5 , Issue.6 , pp. 579-602
    • Berkes, P.1    Wiskott, L.2
  • 3
    • 0035362693 scopus 로고    scopus 로고
    • Sequential extraction of minor components
    • DOI 10.1023/A:1011388608203
    • T. Chen, S.I. Amari, and N. Murata. Sequential extraction of minor components. Neural Processing Letters, 13(3):195-201, 2001. (Pubitemid 32599409)
    • (2001) Neural Processing Letters , vol.13 , Issue.3 , pp. 195-201
    • Chen, T.1    Amari, S.-I.2    Murata, N.3
  • 4
    • 34548412214 scopus 로고    scopus 로고
    • Slowness and sparseness lead to place, head-direction, and spatial-view cells
    • M. Franzius, H. Sprekeler, and L. Wiskott. Slowness and sparseness lead to place, head-direction, and spatial-view cells. PLoS Computational Biology, 3(8):e166, 2007.
    • (2007) PLoS Computational Biology , vol.3 , Issue.8
    • Franzius, M.1    Sprekeler, H.2    Wiskott, L.3
  • 7
    • 78049417739 scopus 로고    scopus 로고
    • Reinforcement learning on slow features of high-dimensional input streams
    • R. Legenstein, N. Wilbert, and L. Wiskott. Reinforcement learning on slow features of high-dimensional input streams. PLoS Computational Biology, 6(8), 2010.
    • (2010) PLoS Computational Biology , vol.6 , Issue.8
    • Legenstein, R.1    Wilbert, N.2    Wiskott, L.3
  • 8
    • 0020464111 scopus 로고
    • A simplified neuron model as a principal component analyzer
    • DOI 10.1007/BF00275687
    • E. Oja. Simplified neuron model as a principal component analyzer. Journal of mathematical biology, 15(3):267-273, 1982. (Pubitemid 13209700)
    • (1982) Journal of Mathematical Biology , vol.15 , Issue.3 , pp. 267-273
    • Oja, E.1
  • 9
    • 0026954958 scopus 로고
    • Principal components, minor components, and linear neural networks
    • E. Oja. Principal components, minor components, and linear neural networks. Neural Networks, 5(6):927-935, 1992. (Pubitemid 23581250)
    • (1992) Neural Networks , vol.5 , Issue.6 , pp. 927-935
    • Oja, E.1
  • 10
    • 34548456303 scopus 로고    scopus 로고
    • Convergence analysis of a simple minor component analysis algorithm
    • DOI 10.1016/j.neunet.2007.07.001, PII S0893608007000962
    • D. Peng, Z. Yi, and W. Luo. Convergence analysis of a simple minor component analysis algorithm. Neural Networks, 20(7):842-850, 2007. (Pubitemid 47361678)
    • (2007) Neural Networks , vol.20 , Issue.7 , pp. 842-850
    • Peng, D.1    Yi, Z.2    Luo, W.3
  • 11
    • 0009305378 scopus 로고
    • Discovering predictable classifications
    • J. Schmidhuber and D. Prelinger. Discovering predictable classifications. Neural Computation, 5(4):625-635, 1993.
    • (1993) Neural Computation , vol.5 , Issue.4 , pp. 625-635
    • Schmidhuber, J.1    Prelinger, D.2
  • 15
    • 0036546660 scopus 로고    scopus 로고
    • Slow feature analysis: Unsupervised learning of invariances
    • Laurenz Wiskott and Terrence Sejnowski. Slow feature analysis: Unsupervised learning of invariances. Neural Computation, 14(4):715-770, 2002.
    • (2002) Neural Computation , vol.14 , Issue.4 , pp. 715-770
    • Wiskott, L.1    Sejnowski, T.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.