· Theoretical principles of algorithms for statistical measurements, signal identification, simulation and prediction, statistical measurement systems, statistical testing grounds, the method of modelletheque for solving these problems, new characteristics of random signals invariant to any monotone one-to-one transformation of signals have been developed.
· Procedures, mathematical methods, algorithms and software for automatic identification of empirical regularities, identification of images under a limited sampling size as well as data analysis under characteristics heterogeneity, poor representation of the sampling, presence of noises, errors and blanks have been elaborated.
· Specific classes of computer systems have been designed and implemented for the acquisition and processing of uniform and different-type experimental data and for solving various application problems, e.g. expert and neuron computer systems, multi-purpose partner systems such as OTEKS, EKSNA, ASSOD, etc.
· Various application problems have been solved, among them engineering diagnostics, monitoring of the population health, forecasting in power engineering, in technological, economic, agricultural and other areas.
The results of these investigations were presented at more than 250 International and All-Russian conferences and symposia, IFAC, LAPR, AL, IFIP, IMECO congresses and symposia included. They were also implemented as automatic and automated processing systems for management, control and measurement of experimental data and introduced into 34 industrial enterprises and organizations. Fifteen All-Russian research symposia on statistical analysis of signals, seventeen All-Russian workshops on “Automatic Recognition of Audio Images” (ARAI) and four All-Russian conferences on “Method of Regularity Identification” (MRI) were held.