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Recent Advances in Non-stationary Signal Processing Based on the Concept of Recurrence Plot Analysis

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Translational Recurrences

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 103))

Abstract

This work concerns the analysis of non-stationary signals using Recurrence Plot Analysis concept. Non-stationary signals are present in real-life phenomena such as underwater mammal’s vocalizations, human speech, ultrasonic monitoring, detection of electrical discharges, transients, wireless communications, etc. This is why a large number of approaches for non-stationary signal analysis are developed such as wavelet analysis, higher order statistics, or quadratic time-frequency analysis. Following the context, the methods defined around the concept of Recurrence Plot Analysis (RPA) constitute an interesting way of analyzing non-stationary signals and, particularly, the transient ones. Starting from the phase space and the recurrence matrix, new approaches [the angular distance, recurrence-based autocorrelation function (ACF), average-magnitude difference function (AMDF) and time-distributed recurrence (TDR)] are introduced in order to extract information about the non-stationary signals, specific to different applications. Comparisons with existing analysis methods are presented, proving the interest and the potential of the RPA-based approaches.

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Author information

Authors and Affiliations

  1. GIPSA-lab, Grenoble Institute of Technology, Saint-Martin-d’Hères, France

    Cornel Ioana, Angela Digulescu & Ion Candel

  2. Military Technical Academy, Bucharest, Romania

    Angela Digulescu & Alexandru Serbanescu

  3. University of South-East Europe “Lumina”, Bucharest, Romania

    Alexandru Serbanescu

  4. University of Pitesti, Pitesti, Romania

    Florin-Marian Birleanu

Authors
  1. Cornel Ioana
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  2. Angela Digulescu
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  3. Alexandru Serbanescu
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  4. Ion Candel
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  5. Florin-Marian Birleanu
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Corresponding author

Correspondence to Cornel Ioana .

Editor information

Editors and Affiliations

  1. Potsdam Institute for Climate Impact Res, Potsdam, Germany

    Norbert Marwan

  2. Dept. of Psychology, University of Cincinnati, Cincinnati, Ohio, USA

    Michael Riley

  3. Istituto Superiore di Sanita, Rome, Italy

    Alessandro Giuliani

  4. Loyola University Chicago, Stritch School of Medicine, Health Sciences Division,Dept. of Cell and Molecular Physiology, Maywood, Illinois, USA

    Charles L. Webber, Jr.

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Ioana, C., Digulescu, A., Serbanescu, A., Candel, I., Birleanu, FM. (2014). Recent Advances in Non-stationary Signal Processing Based on the Concept of Recurrence Plot Analysis. In: Marwan, N., Riley, M., Giuliani, A., Webber, Jr., C. (eds) Translational Recurrences. Springer Proceedings in Mathematics & Statistics, vol 103. Springer, Cham. https://doi.org/10.1007/978-3-319-09531-8_5

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