Theoretical Study of Multiscale Permutation Entropy on Finite-Length Fractional Gaussian Noise

2018 ◽  
Author(s):  
Antonio Davalos ◽  
Meryem Jabloun ◽  
Philippe Ravier ◽  
Olivieri Buttelli
Keyword(s):  
Finite Length ◽  
Gaussian Noise ◽  
Theoretical Study ◽  
Permutation Entropy ◽  
Fractional Gaussian Noise

Permutation entropy of fractional Brownian motion and fractional Gaussian noise

2008 ◽  
Vol 372 (27-28) ◽  
pp. 4768-4774 ◽  
Author(s):  
L. Zunino ◽  
D.G. Pérez ◽  
M.T. Martín ◽  
M. Garavaglia ◽  
A. Plastino ◽  
...  
Keyword(s):  
Brownian Motion ◽  
Fractional Brownian Motion ◽  
Gaussian Noise ◽  
Permutation Entropy ◽  
Fractional Gaussian Noise

Fractional Brownian motion, fractional Gaussian noise, and Tsallis permutation entropy

2008 ◽  
Vol 387 (24) ◽  
pp. 6057-6068 ◽  
Author(s):  
L. Zunino ◽  
D.G. Pérez ◽  
A. Kowalski ◽  
M.T. Martín ◽  
M. Garavaglia ◽  
...  
Keyword(s):  
Brownian Motion ◽  
Fractional Brownian Motion ◽  
Gaussian Noise ◽  
Permutation Entropy ◽  
Fractional Gaussian Noise

scholarly journals Generalized Wavelet Fisher’s Information of1/fαSignals

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Julio Ramírez-Pacheco ◽  
Homero Toral-Cruz ◽  
Luis Rizo-Domínguez ◽  
Joaquin Cortez-Gonzalez
Keyword(s):  
Fisher Information ◽  
Gaussian Noise ◽  
Structural Breaks ◽  
Wavelet Domain ◽  
Fractional Gaussian Noise ◽  
Domain Definition ◽  
Potential Applications ◽  
Definition Of ◽  
The Time Domain ◽  
Fisher's Information

This paper defines the generalized wavelet Fisher information of parameterq. This information measure is obtained by generalizing the time-domain definition of Fisher’s information of Furuichi to the wavelet domain and allows to quantify smoothness and correlation, among other signals characteristics. Closed-form expressions of generalized wavelet Fisher information for1/fαsignals are determined and a detailed discussion of their properties, characteristics and their relationship with waveletq-Fisher information are given. Information planes of1/fsignals Fisher information are obtained and, based on these, potential applications are highlighted. Finally, generalized wavelet Fisher information is applied to the problem of detecting and locating weak structural breaks in stationary1/fsignals, particularly for fractional Gaussian noise series. It is shown that by using a joint Fisher/F-Statistic procedure, significant improvements in time and accuracy are achieved in comparison with the sole application of theF-statistic.

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