Abstract
In this paper, a technique is proposed to process and analyze noisy periodic signals recorded at discrete moments of time. The technique includes two stages: (a) signal quality improvement (processing) with the use of weighted order statistics filters, and (b) cluster analysis of processing results. Basic definitions and specific features of this type of filtration are given, as well as formulations and definitions of cluster analysis, which enable problems to be stated for periodic signal analysis. The efficiency of cluster analysis with weighted order statistics filters is proved based on results of numerical modeling of a noisy frequency-modulated signal.
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