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Volumn 8, Issue 4, 1995, Pages 525-535

Nonlinear higher-order statistical decorrelation by volume-conserving neural architectures

Author keywords

Factorial learning; Nonlinear decorrelation; Volume conserving architectures

Indexed keywords

COMPUTER ARCHITECTURE; CORRELATION METHODS; INFORMATION THEORY; LEARNING SYSTEMS; MATHEMATICAL MODELS; MATHEMATICAL TRANSFORMATIONS; PROBABILITY; STATISTICAL METHODS; TENSORS;

EID: 0029013513     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/0893-6080(94)00108-X     Document Type: Article
Times cited : (79)

References (22)
  • 10
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    • Product units A computationally powerful and biologically plausible extension to backpropagation networks
    • (1989) Neural Computation , vol.1 , pp. 133-142
    • Durbin1    Rumelhart2
  • 13
    • 0023981750 scopus 로고
    • Self-organization in a perceptual network
    • (1988) Computer , vol.21 , pp. 105
    • Linsker1
  • 14
    • 0000353243 scopus 로고
    • How to generate ordered maps by maximizing the mutual information between input and output signals
    • (1989) Neural Computation , vol.1 , pp. 402-411
    • Linsker1
  • 15
    • 0001525549 scopus 로고
    • Local synaptic learning rules suffice to maximize mutual information in a linear network
    • (1992) Neural Computation , vol.4 , pp. 691-702
    • Linsker1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.