The Signal-to-Interference ratio (SIR) has been highlighted in the literature to be a most eecient criterion for several methods aiming at reducing the eeects of cochannel interference, e.g. diversity reception, dynamic channel allocation and power control. In this paper we address the problem on how to obtain fast and accurate measurements of this parameter in a practical context. We develop a...

In using acoustic emissions (AE) for mechanical diagnostics, one major problem is the differentiation of events due to crack growth in a component from noise of various origins. This work presents two algorithms for automatic clustering and separation of AE events based on multiple features extracted from experimental data. The first algorithm consists of two steps. In the first step, the noise...

We discuss the reproducing kernel structure in shift-invariant spaces and the weighted shift-invariant spaces, and obtain the reconstruction formula in time-warped weighted shift-invariant spaces, then apply them to a spline subspace. In the spline subspace, we give a reconstruction formula in a time-warped spline subspace. 1. Introduction. The problem of reconstruction of a function f has been...

This paper discusses the problem of detecting subspace signals in structured interference plus compound Gaussian sea clutter with persymmetric structure. The is represented by a process wherein texture obeys inverse distribution. lies known subspace, which independent target signal subspace. By resorting to two-step generalized likelihood ratio test, Rao, and Wald design criteria, three adaptiv...

| In this paper, we investigate the noise suppression performance of a novel adaptive lter based on sub-space methods. In contrast to conventional subspace lters, this approach requires no eigenvalue or singular value decomposition. Therefore, our adaptive subspace lter can be implemented for real-time operation using general purpose digital signal processors. In addition, only the noisy signal...

There are various image filtering approaches in computer vision and image processing that are effective for some types of noise, but they invariably make certain assumptions about the properties of the signal and/or noise which lack the generality for diverse image noise reduction. This study describes a novel generalised guided image filtering method with the reference image generated by signa...

A blind deconvolution algorithm is introduced. The channel parameters are identi ed based on Maximum Likelihood (ML) criterion and the desired input is estimated using minimum variance estimation. Simulation results show the e cacy of our method. Its estimation error is usually less than other algorithms. Its rate of convergence is su ciently high and compete the others. Although, the algorithm...

Semiparametric estimation of the signal subspace∗ Denis Belomestny, Vladimir Panov, Vladimir Spokoiny 1 — Laboratory for Structural Methods of Data Analysis in Predictive Modeling (MIPT) and University Duisburg-Essen, [email protected] 2 — Laboratory for Structural Methods of Data Analysis in Predictive Modeling (MIPT) and University Duisburg-Essen, [email protected] 3 — Labor...

We prove the existence of a smoothing for toroidal crossing space under mild assumptions. By linking log structures with infinitesimal deformations, result receives very compact form normal spaces. The main approach is to study that are incoherent on subspace codimension two and Hodge-de Rham degeneration theorem such spaces which also settles conjecture by Danilov. show homotopy equivalence be...

a r t i c l e i n f o a b s t r a c t This paper presents a new time domain noise reduction approach based on Singular Value Decomposition (SVD) technique. In the proposed approach, the noisy signal is initially represented in a Hankel Matrix. Then SVD is applied on the Hankel Matrix to divide the data into signal subspace and noise subspace. Since singular vectors are the span bases of the mat...