The article "Algorithms for Generating Equivalent Normalized Correlation Matrices of Noisy Random Signals" by Academician Telman Aliyev, Advisor of ANAS, Professor Naila Musayeva, DSc (Eng), Head of the Laboratory of Identification of Stochastic Processes, and Narmin Rzayeva, PhD (Eng), has been published in the prestigious journal Cybernetics and Systems Analysis.
The authors demonstrate that signals in control objects are usually various physical quantities such as temperature, pressure, vibration, etc. Therefore, when solving problems of control, diagnostics and identification, it becomes necessary to generate normalized correlation matrices. The difficulties of generating normalized correlation matrices of noisy input-output signals of technical objects are analyzed. Algorithms for determining equivalent readings of the noise and useful signal are proposed and the possibility of their use for generating normalized correlation matrices equivalent to the correlation matrices of useful signals of noisy random processes is shown. It is shown that the procedure of the generating normalized correlation matrices is substantially simplified in this case and the error of their elements significantly decreases.