Gaussian filter has been used extensively in signal image processing for many years. Gaussian or Gaussian derivative filtering is in several ways optimal for applications requiring low-pass filters or running averages. In this paper, a highly efficient noise removing technique based on a modified dynamic Gaussian filter is introduced. Called smooth filter, the Gaussian filter is known to be mor...

The noise cancellation should be the first step of each signal processing device. The most difficult type of noise which should be suppressed is an impulsive type of noise. The group of nonlinear robust filter successfully supress such noise. The aim of this work is to present a new approach to myriad filter computation and its application in biomedical signal processing. This new method is bas...

In this paper we present a unified comparison of the performance of four detection techniques for centralized data-fusion cooperative spectrum sensing in cognitive radio networks under impulsive noise, namely, the eigenvalue-based generalized likelihood ratio test (GLRT), the maximum-minimum eigenvalue detection (MMED), the maximum eigenvalue detection (MED), and the energy detection (ED). We c...

Abstract— The direct sequence-code division multiple accesses (DS-CDMA) signals are transmitted over multipath channels that introduce fading and shadowing. Combined effect of multipath fading and shadowing along with multiple access interference (MAI) and inter-symbol interference (ISI) worsens the system performance. Further, experimental results have confirmed the presence of impulsive nonGa...

Many different classes of filters have been proposed for removing noise from images (Astola & Kuosmanen, 1997; Bovik, 2000; Kotropoulos & Pitas, 2001). They are classified into several categories depending on specific applications. Linear filters are efficient for Gaussian noise removal but often distort edges and have poor performance against impulsive noise. Nonlinear filters are designed to ...

This paper presents a new performance enhancement method of information-theoretic learning (ITL) based blind equalizer algorithms for ISI communication channel environments with a mixture of AWGN and impulsive noise. The Gaussian kernel of Euclidian distance (ED) minimizing blind algorithm using a set of evenly generated symbols has the net effect of reducing the contribution of samples that ar...

Many approaches to image restoration are aimed at removing either Gaussian or uniform impulsive noise. This is because both types of degradation processes are distinct in nature, and hence they are easier to manage when considered separately. Nevertheless, it is possible to find them operating on the same image, which produces a hard damage. This happens when an image, already contaminated by G...

Robust diffusion algorithms based on the maximum correntropy criterion(MCC) are developed to address the distributed networks estimation issue in impulsive(long-tailed) noise environments. The cost functions used in distributed network estimation are in general based on the mean square error (MSE) criterion, which is optimal only when the measurement noise is Gaussian. In non-Gaussian situation...

An analytic model á la Middleton of the impulsive noise component in the data of interferometric gravitational wave detectors is proposed, based on an atomic representation of glitches. A fully analytic characterization of the coherent network data analysis algorithm proposed by Rakhmanov and Klimenko is obtained, for the simplest relevant case of triggered detection of unmodeled gravitational ...