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Dynamics Of Fully Connected Neural Networks With Sign Constraints

Author

Listed:
  • M. GUSSO

    (Dipartimento di Fisica dell’Universita’ di Bari, Via Amendola 173, 70126 Bari, Italy)

  • C. MARANGI

    (Dipartimento di Fisica dell’Universita’ di Bari, Via Amendola 173, 70126 Bari, Italy;
    Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Via Amendola 173, 70126 Bari, Italy)

  • G. NARDULLI

    (Dipartimento di Fisica dell’Universita’ di Bari, Via Amendola 173, 70126 Bari, Italy;
    Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Via Amendola 173, 70126 Bari, Italy)

  • G. PASQUARIELLO

    (Istituto Elaborazione Segnali e Immagini – C.N.R., Via Amendola 173, 70126 Bari, Italy)

Abstract

We consider fully connected neural networks near saturation, trained by a modified Edinburgh algorithm, with sign constraints on the synaptic couplings. We study the domains of attraction of the stored patterns for both the balanced and the unbalanced case (excess of positive over negative constraints). A comparison with the dilute network is also included.

Suggested Citation

  • M. Gusso & C. Marangi & G. Nardulli & G. Pasquariello, 1992. "Dynamics Of Fully Connected Neural Networks With Sign Constraints," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 3(06), pages 1221-1233.
    • Handle: RePEc:wsi:ijmpcx:v:03:y:1992:i:06:n:s0129183192000841
    DOI: 10.1142/S0129183192000841
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