Based on artificial neural networks, cellular automaton, deformable templates methods, new mathematical methods and algorithms for fast and reliable experimental data processing have been proposed . The developed codes allow to solve such problems as event identification, track recognition , noise removal. The created programs have been included in the software for data analysis of the experiments DISTO, FOBOS , SINDRUM , EXCHARM , STAR, CERES/NA-45, ATLAS. So, programs implementing the robust algorithm for the fast circle fit after extensive tests on real data of the CERES experiment were included in the basic software of this experiment . A model of second-level trigger, to be applied for track recognition, in searching for secondary vertex, and for identifying the secondary particles is realized now on the basis of 4-RISC processors, which are used in the spectrometer DISTO for data acquisition and on-line analysis . New programs for track recognition were developed. The developed software is successfully used for JINR experiments at U-70 (Protvino, Russia) and LHC (Geneva, Switzerland) in real time monitoring, experimental data processing and simulation of detector performance.