Showing papers on "Wavelet transform modulus maxima method published in 2001"
TL;DR: It is shown that the degree of multifractality defined as a width of singularity spectrum can be successfully used as a measure of complexity both in the case of periodic and aperiodic (stochastic or chaotic) input signals.
Abstract: We use a multifractal formalism to study the effect of stochastic resonance in a noisy bistable system driven by various input signals. To characterize the response of a stochastic bistable system we introduce a new measure based on the calculation of a singularity spectrum for a return time sequence. We use wavelet transform modulus maxima method for the singularity spectrum computations. It is shown that the degree of multifractality defined as a width of singularity spectrum can be successfully used as a measure of complexity both in the case of periodic and aperiodic (stochastic or chaotic) input signals. We show that in the case of periodic driving force, singularity spectrum can change its structure qualitatively becoming monofractal in the regime of stochastic synchronization. This fact allows us to consider the degree of multifractality as a new measure of stochastic synchronization also. Moreover, our calculations have shown that the effect of stochastic resonance can be catched by this measure even from a very short return time sequence. We use also the proposed approach to characterize the noise-enhanced dynamics of a coupled stochastic neurons model.
61 citations
23 Sep 2001
TL;DR: In this article, the authors studied the R-R variability of five young and five elderly subjects for multi-fractal behavior using a partition function method, obtained using the wavelet transform modulus maxima method, allowed the computation of local Hurst exponents.
Abstract: We have studied the R-R variability of five young and five elderly subjects for multi-fractal behaviour using a partition function method. The partition function, obtained using the wavelet transform modulus maxima method, allowed the computation of local Hurst exponents. The multi-fractal spectrum was obtained from the Hurst exponents using a Legendre transformation. The computations revealed specific values of the Hurst exponent at which the multi-fractal spectrum peaked, with a clear separation between young and elderly subjects. The peaks of the young subjects occurred for Hurst exponents in the range 0.06 to 0.13, whereas the peaks for the elderly subjects were in the range 0.29 to 0.36.
7 citations
TL;DR: In this article, the singularity points in the noise signal can be identified using wavelet transform modulus maxima method, which correspond to moments when a strong scattering of CDW occurs.
1 citations