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The application of methods drawn from nonlinear and stochastic dynamics to the analysis of cardiovascular time series are applied with particular interests in the identification of changes associated with aging. Scale invariant and scale dependent approaches are studied. Using signals measured from healthy adults of all age (16-82 years, 71 men and 47 women), four different approaches to investigate cardiovascular aging are considered: (a) complexity and fractal analysis of heart rate variability (HRV); (b) spectral analysis of HRV using the wavelet transform; (c) spectral analysis of blood flow signals recorded with iontophoresis, using the wavelet transform; and (d) cardiorespiratory synchronization analysis. In (a) detrended fluctuation analysis (DFA) comprises a modified root-mean-square (rms) analysis of a random walk and has been developed to detect the fractal (self-similar) correlation property of non-stationary time series. Approaches (b), (c) and (d) focus on nonlinear oscillatory dynamics. In this approach non-stationarity is perceived as time- variability of oscillatory components. The cardiovascular system is perceived as being composed of many nonlinear oscillators of different physiological origin, interacting with each other and subject to noise. The understanding of coupled nonlinear oscillators has progressed rapidly in recent years, especially after the phase description was established. We show how these ideas can be applied to the cardiovascular system. As a first step in studies (b) and (c), we use wavelet analysis to separate the frequency components of nonlinear oscillations of different physiological origin into six intervals. We discuss the age-related changes in each of these frequency components and show how there changes are related to the results of the DFA. As the second step, we study the interaction between cardiac (I) and respiratory (II) systems, by the application of synchronization analysis. Finally, we present an overview of cardiovascular aging in terms of nonlinear dynamics and identify the further problems that remain to be tackled.