Errors of neural networks

Errors of associative sampling and recognition in neural networks are determined by methods of the general theory of statistical solutions taking into account statistical variation of the input image, the correlation radius of the image, the number of neurons, and the number of images in the memory. The beta-distribution is proposed to be used as the statistics of image variations. The admissibility of the utilization of the distribution is tested by using temporal variations of real scenes as an example. The error in determining the coordinate is found for networks on the basis of optical correlators.