Impedance measurement is a practical method to obtain the impedance characteristic of power electronic equipment (PEE), which important for small-signal stability analysis. In measurement, results may be influenced by external noise. Therefore, it essential study how avoid errors caused To address this issue, paper analyzes suppressing noise interference enhancing signal-to-noise ratio (SNR) an...

MOTIVATION It is widely acknowledged that microarray data are subject to high noise levels and results are often platform dependent. Therefore, microarray experiments should be replicated several times and in several laboratories before the results can be relied upon. To make the best use of such extensive datasets, methods for microarray data fusion are required. Ideally, the fused data should...

A high-resolution seismic image is the key factor for helping geophysicists and geologists to recognize geological structures below subsurface. More more complex geology has challenged traditional techniques resulted in a need powerful denoising methodologies. The deep learning technique shown its effectiveness many different types of tasks. In this work, we used conditional generative adversar...

Impulse and Gaussian are the two most common types of noise that affect digital images due to imperfections in imaging process, compression, storage communication. The conventional filtering approaches, however, reduce image quality terms sharpness resolution while suppressing effects noise. In this work, a machine learning-based structure has been proposed preserves effectively removing Specif...

This paper presents an uncertainty based novel filter that integrates randomness and fuzziness, for extremely corrupted images by salt and pepper impulse noise. In real time work, high computational efficiency is the most important factor while suppressing noise with better edge and detail preservation. The proposed algorithm is bounded with all these aspects. In this scheme, the corrupted pixe...

In this paper a novel approach to the impulsive noise removal in color images is presented. The proposed technique employs the switching scheme based on the impulse detection mechanism using the so called peer group concept. Compared to the vector median filter, the proposed technique consistently yields better results in suppressing both the random-valued and fixed-valued impulsive noise. The ...

Abstract One of the primary purposes seismic stratigraphy is to evaluate components layer relationships within a depositional chronology. Prestack images contain wealth information, such as variations in offset and azimuth event, naturally produce higher-resolution facies analysis results than poststack data. However, prestack data usually suffer from potential unreliability issues due low sign...

We have developed a novel algorithm for integrating source localization and noise suppression based on a probabilistic graphical model of stimulus-evoked MEG/EEG data. Our algorithm localizes multiple dipoles while suppressing noise sources with the computational complexity equivalent to a single dipole scan, and is therefore more efficient than traditional multidipole fitting procedures. In si...

The conventional linear adaptive filters are not effective for discriminating the transient wideband signal components from noise. A recently developed wavelet shrinkage approach is able to maintain the function local regularity while suppressing noise however, it has only been used in function estimation problems. In this paper, a new type of nonlinear filtering method for adaptive noise suppr...