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Volumn 22, Issue 1-3, 1998, Pages 145-156

Constrained PCA techniques for the identification of common factors in data

Author keywords

Multiple causes; Principal factor analysis; Sparse coding; Unsupervised

Indexed keywords

CONSTRAINT THEORY; DATA STRUCTURES; IMAGE CODING; SIGNAL THEORY; SPURIOUS SIGNAL NOISE; STATISTICAL METHODS;

EID: 0032213709     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0925-2312(98)00054-X     Document Type: Article
Times cited : (4)

References (15)
  • 2
    • 0000929221 scopus 로고
    • What is the goal of sensory coding?
    • Field D. What is the goal of sensory coding? Neural Comput. 6:1994;555-601.
    • (1994) Neural Comput. , vol.6 , pp. 555-601
    • Field, D.1
  • 3
    • 0003469401 scopus 로고
    • Ph.D. Thesis, University of Cambridge, Cambridge
    • P. Foldiak, Models of sensory coding, Ph.D. Thesis, University of Cambridge, Cambridge, 1992.
    • (1992) Models of Sensory Coding
    • Foldiak, P.1
  • 4
    • 0005901549 scopus 로고
    • PCA properties of interneurons, from neurobiology to real world computing
    • C. Fyfe, PCA properties of interneurons, from neurobiology to real world computing, proc. Int. Conf. on Artificial Neural Networks, 1993.
    • (1993) Proc. Int. Conf. on Artificial Neural Networks
    • Fyfe, C.1
  • 5
    • 0000852458 scopus 로고    scopus 로고
    • Development of entropy coding in a recurrent network
    • G. Harpur, R. Pragur, Development of entropy coding in a recurrent network, Network 7, 1996.
    • (1996) Network , vol.7
    • Harpur, G.1    Pragur, R.2
  • 6
    • 0031590130 scopus 로고    scopus 로고
    • Generative models for discovering sparse distributed representations
    • Technical Report, University of Toronto, Department of Computer Science, Toronto, a modified version to appear in
    • G. Hinton, Z. Ghahramani, Generative models for discovering sparse distributed representations, Technical Report, University of Toronto, Department of Computer Science, Toronto, a modified version to appear in Philos. Trans. Roy. Soc. B, 1997.
    • (1997) Philos. Trans. Roy. Soc. B
    • Hinton, G.1    Ghahramani, Z.2
  • 7
    • 0028272776 scopus 로고
    • Representation and separation of signals using nonlinear PCA type learning
    • Karhunen J., Joutsensalo J. Representation and separation of signals using nonlinear PCA type learning. Neural Networks. 7(1):1994;113-127.
    • (1994) Neural Networks , vol.7 , Issue.1 , pp. 113-127
    • Karhunen, J.1    Joutsensalo, J.2
  • 10
    • 0002399288 scopus 로고
    • Neural networks, principal components and subspaces
    • Oja E. Neural networks, principal components and subspaces. Int. J. Neural Systems. 1:1989;61-68.
    • (1989) Int. J. Neural Systems , vol.1 , pp. 61-68
    • Oja, E.1
  • 13
    • 0003040479 scopus 로고
    • A multiple cause mixture model for unsupervised learning
    • Saund E. A multiple cause mixture model for unsupervised learning. Neural Comput. 7:1995;51-71.
    • (1995) Neural Comput. , vol.7 , pp. 51-71
    • Saund, E.1
  • 14
    • 0026631909 scopus 로고
    • Competitive hebbian learning: Algorithm and demonstration
    • White R.H. Competitive hebbian learning. Algorithm and demonstration Neural Networks. 5:1992;261-275.
    • (1992) Neural Networks , vol.5 , pp. 261-275
    • White, R.H.1
  • 15
    • 0027206958 scopus 로고
    • Least mean square error reconstruction for self-organizing neural-nets
    • Xu L. Least mean square error reconstruction for self-organizing neural-nets. Neural Networks. 6:1993;627-648.
    • (1993) Neural Networks , vol.6 , pp. 627-648
    • Xu, L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.