Optimizing algebraic and neural methods for information processing in distributed fiber-optical measuring systems
Yu. N. Kulchin, E. V. Zakasovskaya · Optical Memory and Neural Networks · 2010
The paper discusses tomography reconstruction of distributed physical fields by means of fiber optical measuring systems (FOMN) [1] for parallel setup of measuring lines with a small number of scanning directions. The approach whose novelty involves measuring network geometry optimization for further application of neural or algebraic technologies to restore a full image of the functions studied is presented. An alternative to choose and apply an appropriate neural network from the set of several, previously trained neural networks of radial-basic type is investigated [2].