Contemporary methods of data processing in experimental physics
Gennady Alekseevich Ososkov · Physics of Particles and Nuclei Letters · 2008
Three basic methods that are extensively applied at JINR to process recent experimental data are reviewed, namely, robust methods of mathematical statistics, artificial neural networks, and wavelet analysis. This review primarily covers studies in which scientists from the Laboratory of Informational Technologies participated, in particular, in collaborations with the leading centers of physics such as CERN, DESY, BNL, GSI, etc. The main principles of the reviewed methods and the most useful and promising examples of their applications are discussed.