Position-Binary Technology of Statistical Analysis of Cyclic Processes and Noises
It is known that the spectral methods11, 24 are usually used for the experimental analysis of cyclic processes. For example, continuous and discrete technological processes, oil extraction, biological processes, etc. are cyclic processes and the spectral methods and algorithms11, 24, 25 are widely used for their experimental researches. But the signals obtained from many cyclic objects as a rule have complicated form and are accompanied by considerable noise and so the application of the spectral method for solving the problem of diagnostics, identification, etc. in some cases is not effective enough24. For an adequate description of these processes in most cases it is necessary to use the great number of harmonic components with corresponding amplitudes and frequencies that considerabl complicates the analysis and the application of obtained results for solving the corresponding problems24. Thus, in solving the different experimental problems for the considered class of objects there is a need for the development of methods and algorithms allowing us at the same time to decrease the number of components of ‘spectrum’ and also to increase the reliability of obtained results in comparison with the spectral method24
KeywordsFiltration Cross Correlation
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