Synergetic neural network

In this study we shall put forward a synergetic neural network and investigate the association dynamics. The present neuron model is substantially based on a top down formulation of the dynamic rule of an analog neural network in contrast to the conventional framework. It is proved that a complete association can be assured up to the same number of the embedded patterns as the number of neurons. In practice an association process is carried out for practical images with 256 gray scale levels and 256 × 256 size. In addition, a searching process of the embedded patterns is also realised by means of controlling attraction parameters. Finally a stochastic model for the dynamic process is also proposed as an intermediate model between the association and the searching of the embedded patterns. Finally a stochastic property of the present model is characterized by fractal dimension of the excitation level of a neuron.