An implicit finite difference scheme is derived which achieves exact results for the area, centroid, variance, skewness and kurtosis (flatness) of solutions to the unforced advection-diffusion equation ∂ t c + λ c + u ∂ x c − κ ∂ 2 x c = 0. Sufficient conditions for computational stability are that the grid spacing ∆x and time step ∆t be small enough that |u| ∆x κ < 12 1/2 , |u| ∆t ∆x < 1 2 1/2...

We compare independent component analysis (ICA) [Bell and Sejnowski, 1995] to an alternative method [Fisher and Principe, 1996] for blind source separation of instantaneous linear mixtures. The method and its application to blind source separation of instantaneous linear mixtures is reviewed. Empirical results separating sources of varying kurtosis and a limited number of samples are presented....

Introduction In acute to early subacute middle cerebral arterial stroke, the mean diffusivity (MD) is more reduced in white matter (WM) than in gray matter (GM) [1]. Moreover, the temporal evolution of MD and fractional anisotropy (FA) is different for WM and GM with varying degree of WM damage at three months [2]. The apparent diffusion kurtosis (ADK) has previously been proposed for visualiza...

We present a computationally efficient method of separating mixed speech signals. The method uses a recursive adaptive gradient descent technique with the cost function designed to maximize the kurtosis of the output (separated) signals. The choice of kurtosis maximization as an objective function (which acts as a measure of separation) is supported by experiments with a number of speech signal...

This paper deals with the problem of estimating atrial activity during atrial fibrillation periods in the electrocardiogram (ECG). Since the signal of interest differs in kurtosis sign from the dominant sources in the ECG, we propose an independent component analysis method for source extraction based on the different kurtosis sign and extend it with a constraint of spectral concentration in th...

This paper proposes an improved least mean kurtosis (LMK) algorithm based on l0-norm cost for enhancing the filter performance in a sparse system. The LMK adaptive filtering algorithm uses a kurtosis of an estimated error signal to improve the filter performance when the noise contamination is serious. Due to the influence of l0-norm cost, the proposed LMK algorithm ensures a fast convergence r...

INTRODUCTION: MR flow imaging continuously improves the understanding and diagnostics of cardiovascular disease [1]. The most common MR flow imaging method is phase-contrast MRI (PC-MRI) velocity mapping, which estimates the mean velocity of a voxel. However, MR has the ability to do much more advanced flow analysis, including quantification of turbulent flow [2, 3]. The aim of this work was to...

The early fault characteristics of rolling element bearings carried by vibration signals are quite weak because the signals are generally masked by heavy background noise. To extract the weak fault characteristics of bearings from the signals, an improved spectral kurtosis (SK) method is proposed based on maximum correlated kurtosis deconvolution (MCKD). The proposed method combines the ability...

This study extends the authors’ earlier work that addresses the importance of bootstrap methods in computing statistical characteristics of meteorological and climatological datasets. Subsampling confidence intervals for the skewness and kurtosis are developed for nonlinear datasets, for which traditional time series techniques are not applicable. It also provides an example of how to apply sub...

In this paper, we introduce a new approximation for estimating the dynamics of multiserver queues with abandonment. The approximation involves a four-dimensional dynamical system that uses the skewness and kurtosis of the queueing distribution via the Gram Charlier expansion. We show that the additional information captured in the skewness and kurtosis allows us to estimate the dynamics of the ...