The accuracy of the functioning of modern neural networks both in the reproduction mode and in the learning mode remains insufficient for many practical tasks, therefore it is expedient to create new methods and algorithms for processing signals and data in neural environments. The purpose of the work is to create a pattern recognition method based on modified differential Hebb learning to increase the accuracy of the functioning of modern neural networks both in the playback mode and in the learning mode. Modifications of the correlation method of face detection were developed, which made it possible to reduce the total classification error by more than two times. A scheme of the parallel process of face recognition based on 2D and 3D images by the appropriate algorithm is proposed
