Signal waveform extraction in the presence of regular and random noise

Diana Konstantinovna Avdeeva, Oleg Nikolaevich Vylegzhanin, Mariya Aleksandrovna Yuzhakova, Sergey Anatol yevich Rybalka, Michael Georgievich Grigoriev, Nikita Vladimirovich Turushev

Research output: Contribution to journalArticlepeer-review

Abstract

The paper focuses on the problem of the signal waveform extraction in the presence of random and regular noise. The principal component analysis has been proposed to extract the waveform. Assuming that the analyzed signal in the recorded sequence is repeated with a certain periodicity, several portions containing the analyzed signal can be extracted using the "caterpillar" method. The obtained matrix is then subjected to singular value decomposition. It is shown that the waveform is defined by the first left singular vector. Mathematical modeling demonstrates the possibility to extract the waveform of the analyzed signal in the presence of random and regular noise. The model calculations prove the possibility to extract the signal waveform in case the level of random noise and the correlation of the extracted signal and regular noise change within a wide range.

Original languageEnglish
Pages (from-to)377-380
Number of pages4
JournalBiosciences Biotechnology Research Asia
Volume11
DOIs
Publication statusPublished - 1 Nov 2014

Keywords

  • Principal component analysis
  • Regular and random noise
  • Signal analysis
  • Waveform recovery

ASJC Scopus subject areas

  • Biotechnology
  • Agronomy and Crop Science
  • Drug Discovery

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