Model-free stochastic processes studied with q-wavelet-based information tools

D. G. PÉREZ, L. ZUNINO, M. T. MARTIN, M. GARAVAGLIA, A. PLASTINO AND O. A. ROSSO

PHYSICS LETTERS A

Año: 2006 vol. 364

0375-9601

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 q -statistical complexity-statistical complexity