Two-state representations of three-state neural networks
- 7 May 1990
- journal article
- Published by IOP Publishing in Journal of Physics A: General Physics
- Vol. 23 (9) , 1633-1644
- https://doi.org/10.1088/0305-4470/23/9/024
Abstract
The authors investigate to what extent the dynamical behaviour of nets consisting of three-state neurons can be realised in nets using two-state neurons. They find that the generalisation from a two-state neuron to a three-state neuron cannot introduce any new behaviour in the deterministic case, but can do so for noisy nets, even in the zero-noise limit. For those noisy three-state nets which have a Hamiltonian description and a two-state representation they investigate the relationship between the three-state Hamiltonian and the two-state Hamiltonian, and find an interesting level-splitting phenomenon.Keywords
This publication has 7 references indexed in Scilit:
- The mean-field theory of a Q-state neural network modelJournal of Physics A: General Physics, 1989
- Neural networks that use three-state neuronsJournal of Physics A: General Physics, 1989
- Information processing in three-state neural networksJournal of Statistical Physics, 1989
- The equivalence between discrete-spin Hamiltonians and Ising Hamiltonians with multi-spin interactionsJournal of Physics C: Solid State Physics, 1987
- Collective properties of neural networks: A statistical physics approachBiological Cybernetics, 1984
- Neural networks and physical systems with emergent collective computational abilities.Proceedings of the National Academy of Sciences, 1982
- The existence of persistent states in the brainMathematical Biosciences, 1974