DocumentCode
177505
Title
Extending multifractal analysis to negative regularity: P-exponents and P-leaders
Author
Leonarduzzi, R. ; Wendt, Herwig ; Jaffard, S. ; Roux, S.G. ; Torres, M.E. ; Abry, Patrice
Author_Institution
Univ. Nac. de Entre Rios, Entre Rios, Argentina
fYear
2014
fDate
4-9 May 2014
Firstpage
305
Lastpage
309
Abstract
Scale invariance is a widely used concept to analyze real-world data from many different applications and multifractal analysis has become the standard corresponding signal processing tool. It characterizes data by describing globally and geometrically the fluctuations of local regularity, usually measured by means of the Hölder exponent. A major limitation of the current procedure is that it applies only to locally bounded functions or signals, i.e., to signals with positive regularity. The present contribution proposes to characterize local regularity with a new quantity, the p-exponent, that permits negative regularity in data, a widely observed property in real-world data. Relations to Hölder exponents are detailed and a corresponding p-leader multifractal formalism is devised and shown at work on synthetic multifractal processes, representative of a class of models often used in applications. We formulate a conjecture regarding the equivalence between Hölder and p-exponents for a subclass of processes. Even when Hölder and p-exponents coincide, the p-leader formalism is shown to achieve better estimation performance.
Keywords
data analysis; estimation theory; fractals; signal processing; Holder exponent; data analysis; estimation performance; negative regularity; p-exponent; p-leader multifractal formalism; scale invariance; signal processing tool; synthetic multifractal analysis processing; Estimation; Fractals; Signal processing; Standards; Wavelet analysis; Wavelet transforms; estimation performance; multifractal analysis; negative local regularity exponent; scale invariance; wavelet Leaders;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location
Florence
Type
conf
DOI
10.1109/ICASSP.2014.6853607
Filename
6853607
Link To Document