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<p>The authors consider the classification of signals with amplitude and phase shift keying of their parameters when observed against the background of additive Gaussian noise. It is shown that using non-parametric SG-statistics as a predictability index allows for the classification of signals and their distinction within each class. A scale of signals according to their predictability index is proposed, which ranks signals according to their complexity.</p>

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Classification of Signals with Digital Parameter Modulation Using SG-Statistics

  • 期刊论文

  • 发表日期：

    2025年5月31日

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  • P. Kostenko,
  • K. Vasiuta,
  • V. Slobodyanuk,
  • R. Kachaylo

摘要

The authors consider the classification of signals with amplitude and phase shift keying of their parameters when observed against the background of additive Gaussian noise. It is shown that using non-parametric SG-statistics as a predictability index allows for the classification of signals and their distinction within each class. A scale of signals according to their predictability index is proposed, which ranks signals according to their complexity.