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Journal Abstract Search

296 related items for PubMed ID: 15593379

  • 1. Time-oriented hierarchical method for computation of principal components using subspace learning algorithm.
    Jankovic M, Ogawa H.
    Int J Neural Syst; 2004 Oct; 14(5):313-23. PubMed ID: 15593379
    [Abstract] [Full Text] [Related]

  • 2. A new modulated Hebbian learning rule--biologically plausible method for local computation of a principal subspace.
    Jankovic M, Ogawa H.
    Int J Neural Syst; 2003 Aug; 13(4):215-23. PubMed ID: 12964209
    [Abstract] [Full Text] [Related]

  • 3. A Hebbian/Anti-Hebbian Neural Network for Linear Subspace Learning: A Derivation from Multidimensional Scaling of Streaming Data.
    Pehlevan C, Hu T, Chklovskii DB.
    Neural Comput; 2015 Jul; 27(7):1461-95. PubMed ID: 25973548
    [Abstract] [Full Text] [Related]

  • 4. Modulated Hebb-Oja learning rule--a method for principal subspace analysis.
    Jankovic MV, Ogawa H.
    IEEE Trans Neural Netw; 2006 Mar; 17(2):345-56. PubMed ID: 16566463
    [Abstract] [Full Text] [Related]

  • 5. A self-stabilizing MSA algorithm in high-dimension data stream.
    Kong X, Hu C, Han C.
    Neural Netw; 2010 Sep; 23(7):865-71. PubMed ID: 20452742
    [Abstract] [Full Text] [Related]

  • 6. A unified self-stabilizing neural network algorithm for principal and minor components extraction.
    Kong X, Hu C, Ma H, Han C.
    IEEE Trans Neural Netw Learn Syst; 2012 Feb; 23(2):185-98. PubMed ID: 24808499
    [Abstract] [Full Text] [Related]

  • 7. Variational Bayesian mixture model on a subspace of exponential family distributions.
    Watanabe K, Akaho S, Omachi S, Okada M.
    IEEE Trans Neural Netw; 2009 Nov; 20(11):1783-96. PubMed ID: 19770092
    [Abstract] [Full Text] [Related]

  • 8. Principal components analysis competitive learning.
    López-Rubio E, Ortiz-de-Lazcano-Lobato JM, Muñoz-Pérez J, Gómez-Ruiz JA.
    Neural Comput; 2004 Nov; 16(11):2459-81. PubMed ID: 15476607
    [Abstract] [Full Text] [Related]

  • 9. Principal component analysis learning algorithms: a neurobiological analysis.
    Friston KJ, Frith CD, Frackowiak RS.
    Proc Biol Sci; 1993 Oct 22; 254(1339):47-54. PubMed ID: 8265675
    [Abstract] [Full Text] [Related]

  • 10. Point-process principal components analysis via geometric optimization.
    Solo V, Pasha SA.
    Neural Comput; 2013 Jan 22; 25(1):101-22. PubMed ID: 23020106
    [Abstract] [Full Text] [Related]

  • 11. A supervised multi-spike learning algorithm based on gradient descent for spiking neural networks.
    Xu Y, Zeng X, Han L, Yang J.
    Neural Netw; 2013 Jul 22; 43():99-113. PubMed ID: 23500504
    [Abstract] [Full Text] [Related]

  • 12. Uncorrelated multilinear principal component analysis for unsupervised multilinear subspace learning.
    Lu H, Plataniotis KN, Venetsanopoulos AN.
    IEEE Trans Neural Netw; 2009 Nov 22; 20(11):1820-36. PubMed ID: 19789108
    [Abstract] [Full Text] [Related]

  • 13. Convergence analysis of a deterministic discrete time system of Oja's PCA learning algorithm.
    Yi Z, Ye M, Lv JC, Tan KK.
    IEEE Trans Neural Netw; 2005 Nov 22; 16(6):1318-28. PubMed ID: 16342477
    [Abstract] [Full Text] [Related]

  • 14. Recursive principal components analysis.
    Voegtlin T.
    Neural Netw; 2005 Oct 22; 18(8):1051-63. PubMed ID: 16181769
    [Abstract] [Full Text] [Related]

  • 15. Nonbinary associative memory with exponential pattern retrieval capacity and iterative learning.
    Salavati AH, Kumar KR, Shokrollahi A.
    IEEE Trans Neural Netw Learn Syst; 2014 Mar 22; 25(3):557-70. PubMed ID: 24807451
    [Abstract] [Full Text] [Related]

  • 16. A robust subspace algorithm for principal component analysis.
    Weingessel A, Hornik K.
    Int J Neural Syst; 2003 Oct 22; 13(5):307-13. PubMed ID: 14652872
    [Abstract] [Full Text] [Related]

  • 17. Convergence analysis of a simple minor component analysis algorithm.
    Peng D, Yi Z, Luo W.
    Neural Netw; 2007 Sep 22; 20(7):842-50. PubMed ID: 17765471
    [Abstract] [Full Text] [Related]

  • 18. A forecast-based STDP rule suitable for neuromorphic implementation.
    Davies S, Galluppi F, Rast AD, Furber SB.
    Neural Netw; 2012 Aug 22; 32():3-14. PubMed ID: 22386500
    [Abstract] [Full Text] [Related]

  • 19. Regularized variational Bayesian learning of echo state networks with delay&sum readout.
    Shutin D, Zechner C, Kulkarni SR, Poor HV.
    Neural Comput; 2012 Apr 22; 24(4):967-95. PubMed ID: 22168555
    [Abstract] [Full Text] [Related]

  • 20. Getting to know your neighbors: unsupervised learning of topography from real-world, event-based input.
    Boerlin M, Delbruck T, Eng K.
    Neural Comput; 2009 Jan 22; 21(1):216-38. PubMed ID: 19431283
    [Abstract] [Full Text] [Related]

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