2010
DOI: 10.1016/j.camwa.2010.05.010
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A wavelet-based tool for studying non-periodicity

Abstract: This paper presents a new numerical approach to the study of non-periodicity in signals, which can complement the maximal Lyapunov exponent method for determining chaos transitions of a given dynamical system. The proposed technique is based on the continuous wavelet transform and the wavelet multiresolution analysis. A new parameter, the \textit{scale index}, is introduced and interpreted as a measure of the degree of the signal's non-periodicity. This methodology is successfully applied to three classical dy… Show more

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Cited by 89 publications
(112 citation statements)
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“…Moreover, wavelets have been successfully used in the analysis of many chaotic systems [31][32][33]. Non-periodicity as a hallmark of a chaotic behavior could be quantified through scale index analysis [33,34]. Let the continuous wavelet transform (CWT) of a signal 2 fL  with respect to some analyzing wavelet function  be: …”
Section: Resultsmentioning
confidence: 99%
“…Moreover, wavelets have been successfully used in the analysis of many chaotic systems [31][32][33]. Non-periodicity as a hallmark of a chaotic behavior could be quantified through scale index analysis [33,34]. Let the continuous wavelet transform (CWT) of a signal 2 fL  with respect to some analyzing wavelet function  be: …”
Section: Resultsmentioning
confidence: 99%
“…The scale index technique was proposed by Benitez [33]. This technique enables the obtaining of information about the periodic nature of generated number series.…”
Section: Scale Index Methodsmentioning
confidence: 99%
“…In recent years some classical systems, such as the logistic map, Henon map, Bonhoeffer-van der Pol oscillator (Benítez et al, 2010), Rössler system (Akhshani et al, 2014), SMA oscillators and the heartbeat dynamics (Behnia et al, 2013) have been analysed by the Scale index. The wavelet transform of a one-dimensional (1D) signal consists of the development into a basis constructed via solutions like functions called wavelet, using various internal transformations and shifts (Awrejcewicz et al, 2009).…”
Section: A Wavelet-based Scale Indexmentioning
confidence: 99%