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Volumn 13, Issue 6, 2002, Pages 1342-1352

On the discrete-time dynamics of the basic Hebbian neural-network node

Author keywords

Chaos; Dynamical behavior; Hebbian neural networks (NNs); Stochastic approximation

Indexed keywords

APPROXIMATION THEORY; COMPUTATIONAL METHODS; COMPUTER SIMULATION; LEARNING SYSTEMS;

EID: 0036858172     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2002.805752     Document Type: Article
Times cited : (83)

References (20)
  • 1
    • 0001687834 scopus 로고
    • Low-frequency phenomena in dynamical systems with many attractors
    • F.T. Arecchi, R. Badii, and A. Politi, "Low-frequency phenomena in dynamical systems with many attractors," Phys. Rev. A, vol. 29, no. 2, pp. 1006-1009, 1984.
    • (1984) Phys. Rev. A , vol.29 , Issue.2 , pp. 1006-1009
    • Arecchi, F.T.1    Badii, R.2    Politi, A.3
  • 4
    • 0002824293 scopus 로고
    • Asymptotic properties of stochastic approximations with constant coefficients
    • H.J. Kushner and H. Huang, "Asymptotic properties of stochastic approximations with constant coefficients," SIAM J. Contr. Optimization, vol. 19, no. 1, pp. 87-105, 1981.
    • (1981) SIAM J. Contr. Optimization , vol.19 , Issue.1 , pp. 87-105
    • Kushner, H.J.1    Huang, H.2
  • 8
    • 0029265833 scopus 로고
    • A novel approach to the convergence of neural networks for signal processing
    • Mar.
    • R.-W. Liu, Y.-F. Huang, and X.-T. Ling, "A novel approach to the convergence of neural networks for signal processing," IEEE Trans. Circuits Syst., vol. 42, pp. 187-188, Mar. 1995.
    • (1995) IEEE Trans. Circuits Syst. , vol.42 , pp. 187-188
    • Liu, R.-W.1    Huang, Y.-F.2    Ling, X.-T.3
  • 9
    • 0017526570 scopus 로고
    • Analysis of recursive stochastic algorithms
    • Mar.
    • L. Ljung, "Analysis of recursive stochastic algorithms," IEEE Trans. Automat. Contr., vol. AC-22, pp. 551-575, Mar. 1977.
    • (1977) IEEE Trans. Automat. Contr. , vol.AC-22 , pp. 551-575
    • Ljung, L.1
  • 10
    • 0020464111 scopus 로고
    • A simplified neuron model as a principal component analyzer
    • E. Oja, "A simplified neuron model as a principal component analyzer," J. Math. Biol., vol. 15, pp. 267-273, 1982.
    • (1982) J. Math. Biol. , vol.15 , pp. 267-273
    • Oja, E.1
  • 11
    • 0030195987 scopus 로고    scopus 로고
    • A symmetric linear neural network that learns principal components and their variances
    • July
    • F. Peper and H. Noda, "A symmetric linear neural network that learns principal components and their variances," IEEE Trans. Neural Networks, vol. 7, pp. 1042-1047, July 1996.
    • (1996) IEEE Trans. Neural Networks , vol.7 , pp. 1042-1047
    • Peper, F.1    Noda, H.2
  • 12
    • 0029057616 scopus 로고
    • Lyapunov functions for convergence of principal component algorithms
    • M.D. Plumbley, "Lyapunov functions for convergence of principal component algorithms," Neural Networks, vol. 8, no. 1, pp. 11-23, 1995.
    • (1995) Neural Networks , vol.8 , Issue.1 , pp. 11-23
    • Plumbley, M.D.1
  • 13
    • 0000016172 scopus 로고
    • A stochastic approximation method
    • H. Robbins and S. Monro, "A stochastic approximation method," Ann. Math. Statist., vol. 22, pp. 400-407, 1951.
    • (1951) Ann. Math. Statist. , vol.22 , pp. 400-407
    • Robbins, H.1    Monro, S.2
  • 14
    • 0024883243 scopus 로고
    • Optimal unsupervised learning in a single-layer linear feedforward neural network
    • T.D. Sanger, "Optimal unsupervised learning in a single-layer linear feedforward neural network," Neural Networks, vol. 2, pp. 459-473, 1989.
    • (1989) Neural Networks , vol.2 , pp. 459-473
    • Sanger, T.D.1
  • 16
    • 4243779250 scopus 로고
    • Study of a one-dimensional map with multiple basins
    • J. Testa and G.A. Help, "Study of a one-dimensional map with multiple basins," Phys. Rev. A, vol. 28, no. 3, pp. 3085-3089, 1983.
    • (1983) Phys. Rev. A , vol.28 , Issue.3 , pp. 3085-3089
    • Testa, J.1    Help, G.A.2
  • 17
    • 0028496455 scopus 로고
    • Global analysis of Oja's flow for neural networks
    • Sept.
    • W.-Y. Yan, U. Helmke, and J.B. Moore, "Global analysis of Oja's flow for neural networks," IEEE Trans. Neural Networks, vol. 5, pp. 674-683, Sept. 1994.
    • (1994) IEEE Trans. Neural Networks , vol.5 , pp. 674-683
    • Yan, W.-Y.1    Helmke, U.2    Moore, J.B.3
  • 18
    • 0029306642 scopus 로고
    • Dynamical system for computing the eigenvectors associated with the largest eigenvalue of a positive definite matrix
    • May
    • Q. Zhang and Z. Bao, "Dynamical system for computing the eigenvectors associated with the largest eigenvalue of a positive definite matrix," IEEE Trans. Neural Networks, vol. 6, pp. 790-791, May 1995.
    • (1995) IEEE Trans. Neural Networks , vol.6 , pp. 790-791
    • Zhang, Q.1    Bao, Z.2
  • 19
    • 0029378292 scopus 로고
    • Energy function for one-unit oja algorithm
    • Sept.
    • Q. Zhang and Y.W. Leung, "Energy function for one-unit oja algorithm," IEEE Trans. Neural Networks, vol. 6, pp. 1291-1293, Sept. 1995.
    • (1995) IEEE Trans. Neural Networks , vol.6 , pp. 1291-1293
    • Zhang, Q.1    Leung, Y.W.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.