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Nonlinear Properties of Cardiovascular Time Series
1999Nonlinear dynamics are certainly involved in tlie generation and control of cardiovascular signais. The paper presents a methodological and clinical review of nonlinear dynainic analysis in heart rate variability signals (HRV) obtained from normal subjects and pathological cases.
SIGNORINI, MARIA GABRIELLA +1 more
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The Quest for Nonlinearity in Time Series
2012Abstract In this chapter, we review the problem of testing for nonlinearity in time series. First, we discuss the definition and the properties of linear processes and the implications that such properties have on the operational strand. Then, we present and review a tentative classification of the various tests that can be found both in the time ...
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Set membership prediction of nonlinear time series
Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228), 2002A nonlinear prediction method based on a set membership approach is proposed. Such method does not need any assumption about the functional form of the model used for prediction, but uses only some information on its regularity. On the contrary, most of the existing prediction methods need the choice of a model structure and this choice is usually the ...
MILANESE, Mario, NOVARA, Carlo
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REFINEMENTS TO MODEL SELECTION FOR NONLINEAR TIME SERIES
International Journal of Bifurcation and Chaos, 2003Many models of the dynamics of nonlinear time series have large numbers of parameters and tend to overfit. This paper discusses algorithms for selecting the best basis functions from a dictionary for a model of a time series. Selecting the optimal subset of basis functions is typically an NP-hard problem which usually has to be solved by heuristic ...
Tomomichi Nakamura +2 more
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DETECTING NONLINEARITIES IN STATIONARY TIME SERIES
International Journal of Bifurcation and Chaos, 1993In this review we survey methods for detecting nonlinearities in stationary time series. These methods are based on the estimation of so-called correlation integrals. These correlation integrals provide a way of analyzing time series and reveal aspects which are often complementary to the information one obtains from power spectra and autocorrelations.
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Nonlinear Analysis of Physiological Time Series
2009Biological systems and processes are inherently complex, nonlinear and nonstationary, and that is why nonlinear time series analysis has emerged as a novel methodology over the past few decades. The aim of this chapter is to provide a review of main approaches of nonlinear analysis (fractal analysis, chaos theory, complexity measures) in physiological ...
Paraschiv-Ionescu, A., Aminian, K.
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Entropy testing for nonlinearity in time series [PDF]
, 2007 In this paper we propose a novel test for the identification of nonlinear dependence in time series. The approach is based on a combination of a test statistic based on an entropy dependence metric, possessing many desirable properties [1], together with a suitable extension of surrogate data methods, a class of Monte Carlo based tests introduced with ...
GIANNERINI, SIMONE +2 more
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Nonlinearity tests for time series
Biometrika, 1986This paper considers two nonlinearity tests for stationary time series. The idea of Tukey's one degree of freedom for nonadditivity test is generalized to the time series setting. The case of concurrent nonlinearity is discussed in detail. Simulation results show that the proposed tests are more powerful than that of \textit{D. M. Keenan}, ibid. 72, 39-
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Nonlinear Time Series Analysis
2018The recent development of nonlinear time series analysis is primarily due to the efforts to overcome the limitations of linear models such as autoregressive moving-average (ARMA) models of Box and Jenkins (1976) in real applications. Two examples of such limitations are the non-ability to model sudden outbursts and the restriction to symmetry in the ...
Ruey S. Tay, Rong Chen
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FOR NONLINEARITY IN THE HEARTBEAT TIME SERIES
Cybernetics and Systems, 1997Angelo Di Garbo +5 more
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