Optimizing Algebraic and Neural Methods for Information Processing in Distributed Fiber-Optical Measuring Systems

摘要

The paper discusses tomography reconstruction of distributed physical fields by means of fiber optical measuring systems (FOMN) 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.