Goodness of fit test for almost cyclostationary processes

Mohammad Reza Mahmoudi; Mohammad Hossein Heydari; Zakieh Avazzadeh; Kim Hung Pho

doi:10.1016/j.dsp.2019.102597

Goodness of fit test for almost cyclostationary processes

Mohammad Reza Mahmoudi, Mohammad Hossein Heydari, Zakieh Avazzadeh, Kim Hung Pho^*

^*Corresponding author for this work

Department of Applied Mathematics

Research output: Contribution to journal › Article › peer-review

35 Citations (Scopus)

Abstract

This paper is devoted to present a goodness of fit test for discrete-time almost cyclostationary models. The main strategy is based on the spectral support estimation and the application of multiple testing. The results of applying the presented method on simulated and real datasets confirm that the introduced approach acts well in view of power study.

Original language	English
Article number	102597
Journal	Digital Signal Processing: A Review Journal
Volume	96
DOIs	https://doi.org/10.1016/j.dsp.2019.102597
Publication status	Published - Jan 2020

Keywords

Almost cyclostationary
Almost periodically correlated
Detection
Discrete Fourier transform
Multiple testing
Spectral analysis

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10.1016/j.dsp.2019.102597

Cite this

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title = "Goodness of fit test for almost cyclostationary processes",

abstract = "This paper is devoted to present a goodness of fit test for discrete-time almost cyclostationary models. The main strategy is based on the spectral support estimation and the application of multiple testing. The results of applying the presented method on simulated and real datasets confirm that the introduced approach acts well in view of power study.",

keywords = "Almost cyclostationary, Almost periodically correlated, Detection, Discrete Fourier transform, Multiple testing, Spectral analysis",

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note = "Publisher Copyright: {\textcopyright} 2019",

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AU - Pho, Kim Hung

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AB - This paper is devoted to present a goodness of fit test for discrete-time almost cyclostationary models. The main strategy is based on the spectral support estimation and the application of multiple testing. The results of applying the presented method on simulated and real datasets confirm that the introduced approach acts well in view of power study.

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KW - Almost periodically correlated

KW - Detection

KW - Discrete Fourier transform

KW - Multiple testing

KW - Spectral analysis

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Goodness of fit test for almost cyclostationary processes

Abstract

Keywords

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