This article deals with the problem of the statistical performance analysis of the MUSIC (Multiple Signal Classification) algorithm which is an eigen-decomposition based method for the estimation of the angles of arrival of signals received by an array of sensors. In past work the performance of the MUSIC algorithm was studied (via an asymptotic statistical analysis of the algorithm’s null spec...

In 1992 David Donoho has introduced the term denoising in connection with the adaptive nonlinear ...ltering in the discrete wavelets transform domain. Despite its advantages this method is not used yet in the communications ...eld. The goal of this paper is to propose a new denoising method, using another strategy for the threshold selection and another wavelets transform. This new discrete wav...

Background Single-shot (SSH) pulse sequences in CMR are beneficial for rapid image acquisition that is robust to motion, especially in arrhythmic patients or poor breath-holders. However, this fast scanning technique trades scan time for a lower signal-to-noise ratio compared to conventional multi-shot acquisitions. Here we propose a motion-compensated denoising technique that improves the imag...

In this paper we have proposed a novel method for image denoising using local polynomial approximation (LPA) combined with the relative intersection of confidence intervals (RICI) rule. The algorithm performs separable column-wise and row-wise image denoising (i.e., independently by rows and by columns), combining the obtained results into the final image estimate. The newly developed method pe...

Ellipsoid fitting is a widely used technique in 3D shape modeling, which simultaneously estimate the center and orientation of 3D object. This paper explores the limits of performance for the ellipsoid-fitting center estimator. It is shown that the noise in the surface sample data can be approximated by a Gaussian distribution when the signal to noise ratio is high. The Cramér-Rao lower bound i...

The real world signals do not exist without noise. Wavelet Transform based denoising is a powerful method for suppressing noise in signals. In this paper, signal denoising based on Double-Density Discrete Wavelet Transform (DDDWT) and Dual-Tree Discrete Wavelet Transform (DTDWT) methods are implemented with optimum values of threshold point and level of decomposition. Based on the intensity of ...

When we speak in an environment with noise, we often modify our speech production, and speech spoken in noise is generally more intelligible than speech produced in a quiet environment, which is known as the Lombard effect. Our goal is to provide intelligible speech announcements in noisy and/or reverberant public spaces, such as train stations. Thus, the present paper examines whether speech s...