Wavelet Fisher’s Information Measure of 1=f α Signals

Wavelet Fisher’s Information Measure of 1=f α Signals

This article defines the concept of wavelet-based Fisher’s information measure (wavelet FIM) and develops a closed-form expression of this measure for 1=f α signals. Wavelet Fisher’s information measure characterizes the complexities associated to 1=f α signals and provides a powerful tool for their...

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Bibliographic Details
Main Authors: Julio Ramírez-Pacheco, Deni Torres-Román, Luis Rizo-Dominguez, Joel Trejo-Sanchez, Francisco Manzano-Pinzón
Format: Article
Language:English
Published: MDPI AG 2011-09-01
Series:Entropy
Subjects:
1=f α processes
structural breaks
Fisher information
fractal index estimation
fractional Gaussian noise
Online Access:http://www.mdpi.com/1099-4300/13/9/1648/
Description
Summary:This article defines the concept of wavelet-based Fisher’s information measure (wavelet FIM) and develops a closed-form expression of this measure for 1=f α signals. Wavelet Fisher’s information measure characterizes the complexities associated to 1=f α signals and provides a powerful tool for their analysis. Theoretical and experimental studies demonstrate that this quantity is exponentially increasing for α > 1 (non-stationary signals) and almost constant for α < 1 (stationary signals). Potential applications of wavelet FIM are discussed in some detail and its power and robustness for the detection of structural breaks in the mean embedded in stationary fractional Gaussian noise signals studied.
ISSN:1099-4300

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