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Journal of Physical Studies 24(2), Article 2003 [5 pages] (2020)
DOI: https://doi.org/10.30970/jps.24.2003 EVALUATION OF THE DIFFERENCE OF PSEUDORANDOM SIGNAL FROM WHITE NOISE USING A PARAMETER OF ENERGY SPECTRUM MODEL OF THE SIGNAL
Z. A. Kolodiy1
1National University Lviv Polytechnic, Institute of Computer Technologies, Automatics and Metrology,
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In many cases, the shape of a signal determines its information content for the researcher. For example, analysis of the shape of an electrocardiogram, electroencephalogram, etc. allows the specialist to identify certain symptoms of the patient's disease. However, evaluation of the information contained in a signal depends on subjective factors, such as the knowledge and experience of the specialist. This means that the same signal, which has the form of a noise signal, may be interpreted differently by different researchers.
In most cases, real signals are pseudorandom, because they are generated by dynamic systems, which are to some extent deterministic. This raises the question: to what extent is a pseudorandom signal generated by a real system similar to a noise signal? At present, there is no objective indicator to assess the difference between a pseudorandom signal and white noise.
The power spectra of pseudorandom signals have been determined. It has been noted that none of the investigated pseudorandom signals is white noise by its power spectrum, but is similar to flicker noise. A relaxation time $ tau $ and a minimum power spectrum value has been established as parameters of the signal power spectrum model for each of the signals explored. The power spectrum analysis of real pseudorandom signals by the value of the relaxation time $ tau $ makes it possible to hypothesize that every real system ‟noise” has its own colored noise in its own way. The coloring degree can be estimated by the $ tau $ parameter, which is individual for each system. If this hypothesis proves to be correct, then the system can be identified by a predestined relaxation time.
