In this paper, a signal-filtering method based on empirical mode decomposition is proposed.
The filtering method is a fully data-driven approach. A noisy signal is adaptively …

This paper introduces a new signal denoising based on the Empirical mode decomposition (EMD)
framework. The method is a fully data driven approach. Noisy signal is decomposed …

This paper introduces a new signal-filtering, which combines the empirical mode
decomposition (EMD) and a similarity measure. A noisy signal is adaptively broken down into …

BACKGROUND AND PURPOSE: Aging is recognized to originate from a diversity of
mechanisms that blur the limits between normal and pathologic processes. The purpose of this …

In this paper a signal denoising scheme based a multiresolution approach referred to as
Empirical mode decomposition (EMD)[1] is presented. The denoising method is a fully data …

In this paper a new adaptive audio watermarking algorithm based on Empirical Mode
Decomposition (EMD) is introduced. The audio signal is divided into frames and each one is …

A method is presented for fully automated detection of Multiple Sclerosis (MS) lesions in
multispectral magnetic resonance (MR) imaging. Based on the Fuzzy C-Means (FCM) algorithm, …

In this paper, an image segmentation method based on Dempster-Shafer evidence theory is
proposed. Basic probability assignment (bpa) is estimated in unsupervised way using pixels …

This paper provides a review of the Teager–Kaiser (TK) energy operator and its extensions
for signals and images processing. This class of operators possesses simplicity and good …

A novel detection approach of linear FM (LFM) signals, with single or multiple components,
in the time-frequency plane of Teager-Huang (TH) transform is presented. The detection …