Empirical mode decomposition (EMD) is a newly developed tool to analyze nonlinear and non-stationary signals. It is used to decompose any signal into a finite number of time varying subband signals termed as intrinsic mode functions (IMFs). Such data adaptive decomposition is recently used in speech enhancement. This study presents the concept of EMD and its application to advanced speech signa...

Sleep apnea is a growing sleep disorder issue and estimate to affect 7% of the adult population in Malaysia. In this study, the electrical activity of the brain is studied using Electroencephalogram (EEG). The data obtained was then decomposed using three methods; Empirical Mode Decomposition (EMD), Bivariate EMD and finally Ensemble EMD. The Index of Orthogonatility (IO) was obtained which sho...

Image fusion is a fundamental technique for integrating high-resolution panchromatic images and low-resolution multispectral (MS) images. Fused images may enhance image interpretation. Empirical mode decomposition (EMD) is an effective method of decomposing non-stationary signals into a set of intrinsic mode functions (IMFs). Hence, the characteristics of EMD may apply to image fusion technique...

In this paper, a new EMD-Wavelet based model is used to reduce carrier phase errors for precise static GPS positioning. The EMD is a new signal processing method for analysing non-linear time series, which decomposes a time series into a finite and often small number of Intrinsic Mode Functions (IMFs). The decomposition procedure is adaptive and data-driven. The IMFs are stationary which are mo...

In this study, the performance of chirplet signal decomposition (CSD) and empirical mode decomposition (EMD) coupled with Hilbert spectrum have been evaluated and compared for ultrasonic imaging applications. Numerical and experimental results indicate that both the EMD and CSD are able to decompose sparsely distributed chirplets from noise. In case of signals consisting of multiple interfering...

There are some methods to decompose a signal into different components such as: Fourier decomposition and wavelet decomposition. But they have limitations in some aspects. Recently, there is a new signal decomposition algorithm called the Empirical Mode Decomposition (EMD) Algorithm which provides a powerful tool for adaptive multiscale analysis of nonstationary signals. Recent works have demon...

Emerinopathies include diseases caused by EMD gene mutations localized on chromosome X and encoding emerin, an integral protein of the nuclear envelope. The most frequent emerinopathy is the X-linked EmeryDreifuss muscular dystrophy (X-EDMD) that was first reported in the 60ths by Emery and Dreifuss [1]. The disease is characterized by muscle weakness and wasting usually with a humeroperoneal d...

The purpose of this study was to clarify the influence of muscle-tendon complex stretch on electromechanical delay (EMD) in terms of the extent of tendon slack in the human medial gastrocnemius (MG). EMD and MG tendon length were measured at each of five ankle joint angles (-30, -20, -10, 0, and 5 degrees : positive values for dorsiflexion) using percutaneous electrical stimulation and ultrason...

The electronic mood device (EMD) is designed to help answer questions about the variability and dynamics of emotions. It is a small, portable instrument used for repeated recording of moods and feelings. Both construction and operation of the EMD are described. The EMD can best be conceived of as an electronic mood adjective checklist. Persons using the EMD are signaled at designated (e.g., hou...