Model-free stochstic processes studied with q-wavelet-based informational tools

D.G. PEREZ; L.ZUNINO; M.T. MARTIN; A.PLASTINO; O.A.ROSSO

PHYSICS LETTERS A

Año: 2007 p. 259 - 266

0375-9601

Abstract We undertake a model-free investigation of stochastic processes employing q-wavelet based quantifiers, that constitute a generalization of their Shannon counterparts. It is shown that (i) interesting physical information becomes accessible in such a way, (ii) for special q values the quantifiers are more sensitive than the Shannon ones and (iii) there exist an implicit relationship between the Hurst parameter H and q within this wavelet framework.q-wavelet based quantifiers, that constitute a generalization of their Shannon counterparts. It is shown that (i) interesting physical information becomes accessible in such a way, (ii) for special q values the quantifiers are more sensitive than the Shannon ones and (iii) there exist an implicit relationship between the Hurst parameter H and q within this wavelet framework.q values the quantifiers are more sensitive than the Shannon ones and (iii) there exist an implicit relationship between the Hurst parameter H and q within this wavelet framework.H and q within this wavelet framework. © 2006 Elsevier B.V. All rights reserved.2006 Elsevier B.V. All rights reserved. PACS: 02.50.-r; 02.50.Ey; 05.40.-a; 43.60.Hj; 65.40.Gr02.50.-r; 02.50.Ey; 05.40.-a; 43.60.Hj; 65.40.Gr Keywords: Self-similar Gaussian stochastic processes; Fractional Brownian motion; Fractional Gaussian noise; Wavelet analysis; Wavelet q-entropy; WaveletSelf-similar Gaussian stochastic processes; Fractional Brownian motion; Fractional Gaussian noise; Wavelet analysis; Wavelet q-entropy; Wavelet