• No se han encontrado resultados

SOME CASES OF CROSSOVER BEHAVIOR IN HEART INTERBEAT AND ELECTROSEISMIC TIME SERIES

N/A
N/A
Protected

Academic year: 2018

Share "SOME CASES OF CROSSOVER BEHAVIOR IN HEART INTERBEAT AND ELECTROSEISMIC TIME SERIES"

Copied!
11
0
0

Texto completo

Loading

Figure

Fig. 1The log-log of S versus f of a healthy young indi-vidual (32 years old) displays a 1/f-like behavior.
Fig. 4Plot of log⟨L(k)⟩ versus log k of heart interbeatsequences of the same data of Fig
Fig. 9Representative power spectra behavior in the NSchannel: electroseismic crossover.
Fig. 13Spectrum of generalized fractal dimensionsa function of the moment order Dq as q for real data (young andelderly healthy subjects).
+3

Referencias

Documento similar

A conditional sampling technique based on a Fuzzy Clustering algorithm has been applied to the analysis of time series of spanwise vorticity fields obtained from time resolved PIV

In this paper, we study the asymptotic (large time) behavior of a selection-mutation-competition model for a population structured with respect to a phenotypic trait when the rate

Following this idea, the entire time series of biosignals have to be analysed (excluding only artefacts parts) and hypotheses about the development in time have not to be

In sum, we observe some influence of property rights theory variables on exercising control in the cooperative, mainly when focusing on the time horizon of investments and on

In another study, Guisan (2004) uses annual time series data for the period 1960-2002 for a number of countries including China, India and Japan and finds that increases in

In team analysis, games were used as the chronologycal variable for the time series, so the team-related statistics are calculated by game for each team, which provided us

However, this is still a problem far from being solved and in this work we will address it as a classifica- tion problem working with delay vectors of the wind power time series

From that moment on, more proposals emerged focused on offering more efficient algorithms capable of processing larger sets of time series: the Proximity Forest algorithm [LSP +