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Volumn 71, Issue 16-18, 2008, Pages 3544-3552

A new local PCA-SOM algorithm

Author keywords

Local principal component analysis; Neural networks; Self organizing mapping; Unsupervised learning

Indexed keywords

COVARIANCE MATRIX; NEURAL NETWORKS; STRENGTH OF MATERIALS;

EID: 56549117413     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2007.10.004     Document Type: Conference Paper
Times cited : (12)

References (16)
  • 1
    • 0032052508 scopus 로고    scopus 로고
    • Soft vector quantization and the EM algorithm
    • E. Alpaydin Soft vector quantization and the EM algorithm Neural Networks 11 3 1998 467 477
    • (1998) Neural Networks , vol.11 , Issue.3 , pp. 467-477
    • Alpaydin, E.1
  • 2
    • 33644887129 scopus 로고    scopus 로고
    • The parameterless self-organizing map algorithm
    • E. Berglund, and J. Sitte The parameterless self-organizing map algorithm IEEE Trans. Neural Networks 17 2 2006 305 316
    • (2006) IEEE Trans. Neural Networks , vol.17 , Issue.2 , pp. 305-316
    • Berglund, E.1    Sitte, J.2
  • 3
    • 0037972137 scopus 로고    scopus 로고
    • Shape statistics in kernel space for variational image segmentation
    • D. Cremers, T. Kohlberger, and C. Schnörr Shape statistics in kernel space for variational image segmentation Pattern Recognition 36 2003 1929 1943
    • (2003) Pattern Recognition , vol.36 , pp. 1929-1943
    • Cremers, D.1    Kohlberger, T.2    Schnörr, C.3
  • 4
    • 0348139702 scopus 로고    scopus 로고
    • Dimension reduction by local principal component analysis
    • N. Kambhatla, and T.K. Leen Dimension reduction by local principal component analysis Neural Comput. 9 7 1997 1493 1516
    • (1997) Neural Comput. , vol.9 , Issue.7 , pp. 1493-1516
    • Kambhatla, N.1    Leen, T.K.2
  • 6
    • 0345494029 scopus 로고
    • The adaptive-subspace SOM (ASSOM) and its use for the implementation of invariant feature detection
    • F. Fogelman-Soulie P. Galniari EC2 and Cie. Paris
    • T. Kohonen The adaptive-subspace SOM (ASSOM) and its use for the implementation of invariant feature detection F. Fogelman-Soulie P. Galniari Proceedings of the ICANN95, International Conference on Artificial Neural Networks vol. 1 1995 EC2 and Cie. Paris 3 10
    • (1995) Proceedings of the ICANN95, International Conference on Artificial Neural Networks , vol.1 , pp. 3-10
    • Kohonen, T.1
  • 9
    • 0036952542 scopus 로고    scopus 로고
    • Interlocking of learning and orthonormalization in RRLSA
    • R. Möller Interlocking of learning and orthonormalization in RRLSA Neurocomputing 49 1-4 2002 429 433
    • (2002) Neurocomputing , vol.49 , Issue.1-4 , pp. 429-433
    • Möller, R.1
  • 10
    • 8644270422 scopus 로고    scopus 로고
    • An extension of neural gas to local PCA
    • R. Möller, and H. Hoffmann An extension of neural gas to local PCA Neurocomputing 62 2004 305 326
    • (2004) Neurocomputing , vol.62 , pp. 305-326
    • Möller, R.1    Hoffmann, H.2
  • 11
    • 0033640614 scopus 로고    scopus 로고
    • Robust recursive least squares algorithm for principal component analysis
    • S. Ouyang, Z. Bao, and G.-S. Liao Robust recursive least squares algorithm for principal component analysis IEEE Trans. Neural Networks 11 1 2000 215 221
    • (2000) IEEE Trans. Neural Networks , vol.11 , Issue.1 , pp. 215-221
    • Ouyang, S.1    Bao, Z.2    Liao, G.-S.3
  • 12
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear component analysis as a kernel eigenvalue Problem
    • B. Schölkopf, A. Smola, and K.-R. Müller Nonlinear component analysis as a kernel eigenvalue Problem Neural Comput. 10 1998 1299 1319
    • (1998) Neural Comput. , vol.10 , pp. 1299-1319
    • Schölkopf, B.1    Smola, A.2    Müller, K.-R.3
  • 13
    • 0000938157 scopus 로고    scopus 로고
    • Learning continuous attractors in recurrent networks
    • H.S. Seung, Learning continuous attractors in recurrent networks, Adv. Neural Inf. Process. Syst. 10 (1998).
    • (1998) Adv. Neural Inf. Process. Syst. , vol.10
    • Seung, H.S.1
  • 15
    • 0033556788 scopus 로고    scopus 로고
    • Mixtures of probabilistic principal component analyzers
    • M.E. Tipping, and C.M. Bishop Mixtures of probabilistic principal component analyzers Neural Comput. 11 2 1999 443 482
    • (1999) Neural Comput. , vol.11 , Issue.2 , pp. 443-482
    • Tipping, M.E.1    Bishop, C.M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.