Detection of non random phase signal in additive noise with Surrogate Analysis


Téléchargements par mois depuis la dernière année

Plus de statistiques...

Caza-Szoka, M. et Massicotte, D. (2019, May 12-17). Detection of non random phase signal in additive noise with Surrogate Analysis. Dans ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK DOI 10.1109/ICASSP.2019.8682310.

[thumbnail of MASSICOTTE_D_28_POST.pdf]
Télécharger (314kB) | Prévisualisation


The Surrogate Analysis (SA) is known to detect nonlinear signals, non-stationary signals and ARMA systems driven by non-Gaussian processes. This paper adds to address the detection of non-random phase signal, of which the linear phase signal is the best-known example. This is a new interpretation of the SA. In order to highlights the benefits of the interpretation, a new theoretical signals is constructed. The signal has a perfect Gaussian distribution and is not affected by periodic extension and is a linear phase signal. The SA will be shown able to detect this signal in a noise with exactly the same power spectrum. It will be clear that the SA is able to detect phase linearity even when the data is normally distributed. An application of the detection by SA is given regarding very noisy and short time electrocardiogram (ECG) signal and compared to higher order statistics and normality tests for this purpose.

Type de document: Document issu d'une conférence ou d'un atelier
Mots-clés libres: Nonlinear Analysis Hypothesis Testing Detection Bootstrap method Biomedical signal Fractal dimension
Date de dépôt: 09 mai 2022 13:09
Dernière modification: 09 mai 2022 13:09

Actions (administrateurs uniquement)

Éditer la notice Éditer la notice