In this article we investigate the performance of the ICA algorithm AMUSE when applied to images contaminated by noise. The classes of noise we are using have gaussian, multiplicative and impulsive distributions. We find that AMUSE copes surprisingly well with the different types of noise, including multiplicative noise.

The Median-Rational Hybrid Filter (MRHF) has been recently introduced [1][2] as a new class of nonlinear filters and successfully applied to image filtering problems. The main characteristics of the MRHF are the good noise attenuation property in smooth areas and the preservation of edges end details. In fact, in changing areas the noise attenuation is traded for a good response to the change. ...

To address sparse system identification problem in non-Gaussian impulsive noise environment, the recursive generalized maximum correntropy criterion (RGMCC) algorithm with sparse penalty constraints is proposed to combat impulsive-inducing instability. Specifically, a recursive algorithm based on the generalized correntropy with a forgetting factor of error is developed to improve the performan...

The leastmean p-power (LMP) is one of themost popular adaptive filtering algorithms. With a proper p value, the LMP can outperform the traditional least mean square (p = 2), especially under the impulsive noise environments. In sparse channel estimation, the unknown channel may have a sparse impulsive (or frequency) response. In this paper, our goal is to develop new LMP algorithms that can ada...

In this paper, an algorithm for sparse channel estimation, called ‘1-regularized leastabsolutes (‘1-LA), and an algorithm for equalization, called linear least-absolutes (LLA), in non-Gaussian impulsive noise are proposed. The proposed approaches are based on the minimization of the absolute error function, rather than the squared error function. By replacing the standard modulus with the ‘1-mo...

In this paper, we investigate a class of fuzzy CohenGrossberg neural networks with time delays and impulsive effects. By virtue of stochastic analysis, Halanay inequality for stochastic differential equations, we find sufficient conditions for the global exponential square-mean synchronization of the FCGNNs under noise perturbation. In particular, the traditional assumption on the differentiabi...

We investigate the influence of side information of the sender and the receiver on the performance of data transmission systems over impulsive noise channels. The “hidden” side information is the note that the in–phase and the quadrature components of the transmitted signal at a fixed time instant meet the same transmission conditions. The “exposed” side information is received when the impulsi...

Explicit receiver structures for the optimum detection of M-ary orthogonal signals in impulsive noise environments typical of ELF are determined. The resulting optimum structures, while shown to bear some resemblance to that which would have been obtained in the presence of Gaussian noise alone, exhibit an interesting nonlinear behavior. The difficulties in the actual implementation of this rec...

This paper deals with automatic speech recognition robustness for noisy wireless communications. We propose several solutions to improve speech recognition over the cellular network. Two architectures are derived for the recognizer. They are based on Hidden Markov Models (HMMs) adapted to adverse noise conditions. Then two more specific solutions aiming to alleviate GSM cellular network defects...

In this paper a novel approach to the problem of impulsive noise removal in color images based on the nonparametric density estimation is presented. The basic idea behind the new image filtering technique is the maximization of the similarities between pixels in a predefined filtering window. The new method is faster than the standard vector median filter and preserves better edges and fine ima...