Multilayer Neural Network based on Multi-Valued Neurons and the Blur Identification Problem

A multilayer neural network based on multivalued neurons (MLMVN) is a neural network with a traditional feedforward architecture. At the same time this network has a number of specific properties and advantages. Its backpropagation learning algorithm does not require differentiability of the activation function. The functionality of MLMVN is higher than the ones of the traditional feedforward neural networks and a variety of kernel-based networks. Its higher flexibility and faster adaptation to the mapping implemented make possible an accomplishment of complex problems using a simpler network. The MLMVN can be used to solve those non-standard recognition and classification problems that cannot be solved using other techniques. In this paper we use the MLMVN as a tool for the blur identification problem. A prior knowledge about the distorting operator and its parameter is of crucial importance in blurred image restoration.