Abstract: Biomedical signals are commonly recorded with many kinds of noise. One of these is a waveform of the electrical activity of muscles. This “natural” distortion is usually modelled with a white Gaussian noise. In order to suppress such noise a weighted myriad filter is applied. The weighted myriad filter belongs to a class of non-linear filters and requires knowledge about noise impulsi...

A new approach to analyzing and decoding MIMO signaling has been developed for the regular model of non-Gaussion noise, consisting of background and impulse noise named ε-noise. It has been shown that non-Gaussion noise performance is significantly worse than Gaussion noise performance. Simulation results support the suggested theory. Robust in a statistical sense detection rule is suggested fo...

This paper addresses the problem of acoustic source localization in shallow water environment commonly dominated by impulsive noise and multipath phenomenon. Traditionally acoustic source localization with sensors spaced several wavelengths apart involves Time Delay Estimation (TDE) via Generalized Cross-Correlation Phase Transform (GCCPHAT). However multipath signals and impulsive noise in und...

This paper is mainly to deal with the problem of direction of arrival (DOA) estimations of multiple narrow-band sources impinging on a uniform linear array under impulsive noise environments. By modeling the impulsive noise as -stable distribution, new methods which combine the sparse signal representation technique and fractional lower order statistics theory are proposed. In the new algorithm...

To satisfy the smart grid electrical network, communication systems in high-voltage substations have to be installed in order to control equipments. Considering that those substations were not necessarily designed for adding communication networks, one of the most appropriate solutions is to use wireless sensor network (WSN). However, the high voltage transported through the station generates a...

In this paper, a new method for edge detection in presence of impulsive noise based into the use of Support Vector Machines (SVM) is presented. This method shows how the SVM can detect edge in an efficient way. The noisy images are processed in two ways, first reducing the noise by using the SVM regression and then performing the classification using the SVM classification. The results presente...

Data transmission using power line has awaked interest due to many factors: money savings by the use of infrastructure already available; ease of use; possibility to apply new technologies to home appliances and others. Since there is no accepted noise model for power line channel and fewer mathematical formulation to facilitate analytical analysis one way to approach the problem is through Mon...

A robust recursive least-squares (RLS) adaptive filter against impulsive noise is proposed for the situation of an unknown desired signal. By minimizing a saturable nonlinear constrained unsupervised cost function instead of the conventional least-squares function, a possible impulse-corrupted signal is prevented from entering the filter’s weight updating scheme. Moreover, a multi-step adaptive...

This paper investigates the robustness properties of Pearson's rank-variate correlation coefficient (PRVCC) in scenarios where one channel is corrupted by impulsive noise and the other is impulsive noise-free. As shown in our previous work, these scenarios that frequently encountered in radar and/or sonar, can be well emulated by a particular bivariate contaminated Gaussian model (CGM). Under t...

Multiple-input multiple-output (MIMO) has been employed for wireless communications in order to increase the reliability and improve the performance. In this paper MIMO is employed for Power Line Communications (PLC) in an effort to investigate the space diversity gain in PLC systems. It is shown in this paper that in the presence of impulsive noise, a combination of space and time coding is re...