We undertake the study of human EEG-signals by recourse to a wavelet based multiresolution analysis as adapted to an Information-Measure-Scenario. Different information measures are employed. It is shown that non-extensive ones seem to be of particular usefulness. Their use opens up perspectives...

We undertake the study of signals originated in time-dependent nonlinear systems by recourse to a wavelet-based multiresolution analysis as adapted to a nonextensive (Tsallis) scenario. Diverse applications are discussed. It is shown that the Tsallis environment provides one with more detailed...

We undertake the study of EEG-signals by recourse to a wavelet based multiresolution analysis as adapted to an information-measure-scenario. Different information measures are employed. It is shown that non-extensive ones seem to be of particular usefulness.

This paper deals with the automatic detection of slight parameter changes from the analysis of signals generated by nonlinear biological systems. The interest is focused here on investigating particular aspects of the relation between signal analysis and systems dynamics, involving the automatic...

Estimation of complexity is of great interest in nonlinear signal and system analysis. Several complexity measures have been proposed: Lyapunov exponents, Lempel and Ziv, approximate entropy. In the present study, complexity measures derived from Shannon entropy,...