User menu

Hypercubic Structures in Orthogonal Hopfield Models

Bibliographic reference Horn, D. ; Weyers, Jacques. Hypercubic Structures in Orthogonal Hopfield Models. In: Physical review. A, Atomic, molecular, and optical physics, Vol. 36, no. 10, p. 4968-4974 (1987)
Permanent URL
  1. Hopfield J. J., Neural networks and physical systems with emergent collective computational abilities., 10.1073/pnas.79.8.2554
  2. Hopfield J. J., Neurons with graded response have collective computational properties like those of two-state neurons., 10.1073/pnas.81.10.3088
  3. Amit Daniel J., Gutfreund Hanoch, Sompolinsky H., Spin-glass models of neural networks, 10.1103/physreva.32.1007
  4. Amit Daniel J., Gutfreund Hanoch, Sompolinsky H., Storing Infinite Numbers of Patterns in a Spin-Glass Model of Neural Networks, 10.1103/physrevlett.55.1530
  5. Horn D., Weyers J., Information packing in associative memory models, 10.1103/physreva.34.2324
  6. Kanter I., Sompolinsky H., Associative recall of memory without errors, 10.1103/physreva.35.380
  7. L. Personnaz, J. Phys. Lett. (Paris), 46, 359 (1985)
  8. Personnaz L., Guyon I., Dreyfus G., Collective computational properties of neural networks: New learning mechanisms, 10.1103/physreva.34.4217
  9. Horn D., Frustrated spin Hamiltonians with binary input vectors, 10.1103/physreva.33.2595
  10. A. C. Paley, J. Math. Phys., 12, 311 (1933)