Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance

0484841 - ÚFE 2018 RIV US eng J - Článek v odborném periodiku
Poplová, Michaela - Sovka, P. - Cifra, Michal … celkem 4 autorů
Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance.
PLoS ONE. Roč. 12, č. 12 (2017), č. článku e0188622. ISSN 1932-6203. E-ISSN 1932-6203
Grant CEP: GA ČR(CZ) GA13-29294S
Grant ostatní: AV ČR(CZ) SAV-15-22
Program: Bilaterální spolupráce
Institucionální podpora: RVO:67985882
Klíčová slova: Poisson distribution * Photons * Neutrophils
Obor OECD: Electrical and electronic engineering
Impakt faktor: 2.766, rok: 2017

Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal
Trvalý link: http://hdl.handle.net/11104/0279997