Signal Waveform Extraction in the Presence of Regular and Random Noise

Bibliographic Details
Parent link:Biosciences Biotechnology Research Asia
Vol. 11.— 2014.— [P. 377-380]
Corporate Author: Национальный исследовательский Томский политехнический университет (ТПУ) Институт кибернетики (ИК) Кафедра прикладной математики (ПМ)
Other Authors: Avdeeva D. K. Diana Konstantinovna, Vylegzhanin O. N. Oleg Nikolaevich, Yuzhakova M. A. Maria Aleksandrovna, Rybalka S. A. Sergey Anatolyevich, Grigoriev M. G. Mikhail Georgievich, Turushev N. V. Nikita Vladimirovich
Summary:Title screen
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.
Режим доступа: по договору с организацией-держателем ресурса
Language:English
Published: 2014
Subjects:
Online Access:http://dx.doi.org/10.13005/bbra/1489
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=642266
Description
Summary:Title screen
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.
Режим доступа: по договору с организацией-держателем ресурса
DOI:10.13005/bbra/1489