Vladimir E. Bondarenko
Institutef Biochemical Physics, Russian Academy of Scinces
In this paper the processes of self-organization in asymmetric analog neural network model with time delay and under external sinusoidal force are examined. The changes in quantitative characteristics of neural network outputs such as the correlation dimension, largest Lyapunov exponent, Shannon entropy and normalized Shannon entropy are studied as functions of amplitude and frequency of the external force at one-neuron and all-neurons action.The asymmetric analog neural network model with time delay under the study is described by the set of ordinary differential equations. It is obtained from the solution of the differential equations that the neural network model produces signal which have no significant differences from the human-rhythm. The calculation of the correlation dimension shows that its value can be the same for all neurons simultaneously or can be varied from one neuron to another