Self-Organization in a Spin Model of Chaos Neural Network
Abstract
A self-organization model of the Ising spin system is studied in a chaos neural network. The time developments of energies and magnetizations of the spin system are calculated to characterize the dynamics of this model. It is seen that if the control parameters of the chaos neuron are chosen properly, the system can reach a stable pattern which corresponds to the global minimum.
- Publication:
-
Progress of Theoretical Physics Supplement
- Pub Date:
- 2000
- DOI:
- 10.1143/PTPS.138.598
- Bibcode:
- 2000PThPS.138..598T