title: Self-organization of day cycle and hierarchical associative memory in "live" neural network.
abstract: The "live" neural network model is proposed on the basis of "live" neuron model and optimal learning rule. By means of numerical simulation the initial stages of neural network self-organization have been shown: (1) the formation of two activity forms, which are identified with sleep and awaking, and (2) the self-organization of hierarchical associative memory when feeding a receptor excitation to the neural network. The energetic profit of self-organization is demonstrated. The formation of neural ensembles, playing the role of generalized neurons, is obtained.
authors.affiliation: Machines and Tools Institute (Stankin), Moscow, Russia.
authors.forename: L B
authors.initials: LB
authors.lastname: Emelyanov-Yaroslavsky
authors.forename: V I
authors.initials: VI
authors.lastname: Potapov
mesh_terms: D001683:Biological Clocks; D002940:Circadian Rhythm; D008433:Mathematics; D008568:Memory; D016571:Neural Networks, Computer; D009474:Neurons