background common carotid artery (cca) ultrasound with measurement of intima-media thickness (imt) is a safe and noninvasive technique for assessing subclinical atherosclerosis and determining cardiovascular risks. moreover, the pattern of wall thickening in the brachial artery (ba) is rather diffuse compared to the carotid artery and may be a more sensitive indicator of long-term systemic expo...

We address the problem of online de-noising a stream of input points. We assume that the clean data is embedded in a linear subspace. We present two online algorithms for tracking subspaces and, as a consequence, de-noising. We also describe two regularization schemas which improve the resistance to noise. We analyze the algorithms in the loss bound model, and specify some of their properties. ...

The existence of noise has great influence on the real features of observed time series, thus noise reduction in time series data is a necessary and significant task in many practical applications. When using traditional de-noising methods, the results often cannot meet the practical needs due to their inherent shortcomings. In the present paper, first a set of key but difficult wavelet de-nois...

Here it is represented an image analysis technique using both noising & de-noising process. By taking a simple image of different formats we added a noise i. e. Gaussian noise to the particular image and then the calculation of SNR(SIGNAL-TO-NOISE RATIO) and PSNR(PEAK SIGNAL-TO-NOISE RATIO) is performed based on the image formats such as jpeg, png, etc. Although there are various types of noise...

A noiseless ECG identification technology is an emerging new biometric modality. Different techniques for de-noising of ECG signal are prevalent in recent literatures such as Particle Filter (PF), wavelet transforms (WT), Empirical Mode Decomposition (EMD) & Ensemble-EMD Method. In view of the fact that Analysis of ECG signals becomes difficult to inspect the cardiac activity in the presence of...

The widely used Total Variation de-noising algorithm can preserve sharp edge, while removing noise. However, since fixed regularization parameter over entire image, small details and textures are often lost in the process. In this paper, we propose a modified Total Variation algorithm to better preserve smaller-scaled features. This is done by allowing an adaptive regularization parameter to co...

Auto-encoder is a special kind of neural network based on reconstruction. De-noising auto-encoder (DAE) is an improved auto-encoder which is robust to the input by corrupting the original data first and then reconstructing the original input by minimizing the reconstruction error function. And contractive auto-encoder (CAE) is another kind of improved auto-encoder to learn robust feature by int...

Unlike Gaussian noise, Rician noise filtering is more challenging, since this type of noise exists in Functional Magnetic Resonance Imaging (fMRI) data which makes the analysis of fMRI data very difficult for experimental and clinical purposes. To cope with the situation, normally (smoothing) de-noising is done before the analysis of the data using conventional methods like Gaussian filtering a...

In ultrasonic non-destructive testing of materials with a coarse-grained structure the scattering from the grains causes backscattering noise, which masks flaw echoes in the measured signal. Several filtering methods have been proposed for improving the signal-to-noise ratio. In this paper we present a comparative study of methods based on the wavelet transform. Experiments with stationary, dis...

Nowadays, most analytical instruments in modern laboratories are computerized, partly owing to the rapid development of advanced micro-electronic technology. Digitalized spectroscopic data can be exported from these instruments very easily for subsequent signal processing. Raman Spectroscopy is widely recognized as powerful, non-destructive techniques for characterizing materials. The key to re...