Architecture of the neural-like photosensitive system for solution of the fiber-optical tomography problem

In the given article the method of optical information gathering from the fiber-optical measuring network with its subsequent processing is offered. In this method the algorithms of neural-like networks in computation process is introduced. Each sensitive area of the fiber-optical measuring line is associated with the own amplifier. Adjustment of amplifiers gain factors carries out modification of the weighting coefficients of the matrix of connections of the neural network. The training principles to external physical influences are represented. The selection of the type of the neural network for decision of the fiber-optical tomography problem of spatial distribution reconstruction has been considered.