Self-organization of day cycle and hierarchical associative memory in "live" neural network.
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.
Emelyanov-Yaroslavsky
L B
LB
Machines and Tools Institute (Stankin), Moscow, Russia.
Potapov
V I
VI
D001683:Biological Clocks; D002940:Circadian Rhythm; D008433:Mathematics; D008568:Memory; D016571:Neural Networks, Computer; D009474:Neurons