STRONG LAWS FOR RECURRENCE QUANTIFICATION ANALYSIS

Strong Laws for Weighted Sums of Negative Dependent Random Variables

In this paper, we discuss strong laws for weighted sums of pairwise negatively dependent random variables. The results on i.i.d case of Soo Hak Sung [9] are generalized and extended.

Recurrence Quantification Analysis of Financial Markets

Recurrence quantification analysis is a nonlinear time series analysis technique that detects deterministic dependencies in time series. This technique is particularly appropriate for modeling financial time series since it requires no assumptions on stationarity, statistical distribution, and minimum number of observations. This chapter illustrates two applications of recurrence quantification...

Recurrence Quantification Analysis of Surface Electromyograms

In this paper we describe one of the possible application of recurrence plot strategy to the analysis of surface elctromyograms (sEMG). Recurrence quantification analysis (RQA) is an efficient time-series analysis tool pertaining to the class of non-linear dynamics time-domain processing. We analysed sEMG recorded during isometric contractions at constant and linearly varying force. In order to...

Recurrence Quantification Analysis of Nonlinear Dynamical Systems

Recurrence quantification analysis of postural fluctuations.

A technique (recurrence quantification analysis; RQA) for analyzing center of pressure (COP) signals is presented and applied to data obtained by having participants stand with the head forward or sideways and with eyes open or closed. RQA is suitable for short, nonstationary signals and quantifies dynamical (deterministic) structure and nonstationarity. Results indicated that vision affects th...