The objective is to present a method to analyze vocal tremor in sustained speech sounds and compare the results with a perceptual scoring of the degree of tremor. The vocal cycle lengths are tracked by salience analysis and dynamic programming. The cycle length time series is then split into three components by empirical mode decomposition: jitter, tremor and trend. Tremor cues are obtained via...

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Image fusion has emerged as a promising area of research and a bivariate empirical mode decomposition based fusion scheme has recently been proposed in the literature. In this paper, a hybrid fusion scheme combining self-fractional Fourier function (SFFF) decomposition and multivariate empirical mode decomposition is proposed. In the proposed image fusion technique, images to be fused are decom...

Ensemble empirical mode decomposition (EEMD) is a noiseassisted method and also a significant improvement on empirical mode decomposition (EMD). However, the EEMD method lacks a guide to choosing the appropriate amplitude of added noise and its computation efficiency is fairly low. To alleviate the problems of the EEMD method, the improved complementary EEMD method (ICEEMD) was proposed. Furthe...

This paper presents a new time of arrival (TOA) estimation technique using an improved energy detection (ED) receiver based on the empirical mode decomposition (EMD) in an impulse radio (IR) 60 GHz millimeter wave (MMW) system. A threshold is employed via analyzing the characteristics of the received energy values with an extreme learning machine (ELM). The effect of the channel and integration...

For the mode mixing problem caused by intermittency signal in empirical mode decomposition (EMD), a novel filtering method is proposed in this paper. In this new method, the original data is pretreated by using wavelet denoising method to avoid the mode mixture in the subsequent EMD procedure. Because traditional wavelet threshold denoising may exhibit pseudo-Gibbs phenomena in the neighborhood...

The research objective in this paper is to investigate the feasibility and effectiveness of utilizing envelope extraction combining the multi-scale entropy (MSE) analysis for identifying different roller bearing faults. The features were extracted from the angle-domain vibration signals that were measured through the hardware-implemented order-tracking technique, so that the characteristics of ...

This article considers the nonparametric maximum likelihood estimator (MLE) for the joint distribution function of an interval censored survival time and a continuous mark variable. We derive a new explicit formula for the MLE that has both computational and theoretical advantages. Using this formula and the mark specific cumulative hazard function of Huang & Louis (1998), we derive the almost ...

Financial time series are notoriously difficult to analyze and predict, given their non-stationary, highly oscillatory nature. In this study, we evaluate the effectiveness of the Ensemble Empirical Mode Decomposition (EEMD), the ensemble version of Empirical Mode Decomposition (EMD), at generating a representation for market indexes that improves trend prediction. Our results suggest that the p...