Period-two cycles in a feedforward layered neural network model with symmetric sequence processing.
The effects of dominant sequential interactions are investigated in an exactly solvable feedforward layered neural network model of binary units and patterns near saturation in which the interaction consists of a Hebbian part and a symmetric sequential term. Phase diagrams of stationary states are obtained and a phase of cyclic correlated states of period two is found for a weak Hebbian term, independently of the number of condensed patterns c.
Metz
F L
FL
Instituto de Física, Universidade Federal do Rio Grande do Sul, Caixa Postal 15051, 91501-970 Porto Alegre, Brazil.
Theumann
W K
WK
D000465:Algorithms; D000818:Animals; D001703:Biophysics / Q000379:methods*; D003198:Computer Simulation; D006801:Humans; D008954:Models, Biological; D008956:Models, Chemical; D008959:Models, Neurological; D015233:Models, Statistical; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D013269:Stochastic Processes