Gearbox is an important mechanical device to transmit power. In order to ensure the normal operation of gearbox under the condition of top load, high efficiency and high precision, it’s necessary to extract fault feature information using signal processing method and to further analyze and research gearbox fault. In the paper an improved de-noising method based on de-noising of singular value d...

A new approach to modified S-transform based non-stationary power signal de-noising is presented in this paper. Modified S-transform is employed in de-noising techniques to separate high frequency noise which is prevalent in practical signals like power disturbance signals from the low frequency undistorted signals. In this we have tried to bring out the advantage of the modified S-transform an...

Magnetic resonance images acquired with high temporal resolution often exhibit large noise artifacts, which arise from physiological sources as well as from the acquisition hardware. These artifacts can be detrimental to the quality and interpretation of the time-course data in functional MRI studies. A class of wavelet-domain de-noising algorithms estimates the underlying, noise-free signal by...

This paper proposes time-frequency analysis of EEG spectrum and wavelet analysis in EEG de-noising. In this paper, the basic idea is to use the characteristics of multi-scale multi-resolution, using four different thresholds to wipe off interference and noise after decomposition of the EEG signals. By analyzing the results, understanding the effects of four different methods, it comes to a conc...

As to the hybrid noise characteristic, a mixed de-noising method is hereby proposed in combination with the median filter and the wavelet transform. Firstly, conduct the median filter to the pending image; then apply an improved threshold function to the wavelet transform (WT) to eliminate noise; finally, adopt Signal Noise Ratio (SNR) to evaluate the image de-noising effect. The experiment res...

The s-transform is a variable window of STFT and extension of wavelet. This paper discussed the principle and method of Wavelet De-noising, reduced noise of pulse signal based on wavelet. It is shown that wavelet de-noising can eliminate most noise, and preserve effectively sudden change of signal. This paper analyzed and compared the effect of denoising of pulse signal in different ways all st...

There are various de-noising algorithms and optimization methods for different signal and noise characteristics. However, the signals used in real application may have deviations from the model. For example: signal and/or noise may not be stationary or a proper model for them may not be available. MCG (magnetocardiography) is an example signal, where conventional de-noising methods are not givi...

The purpose of the ct-image de-noising is an important research topic both in image processing and biomedical engineering. Independent component analysis (ica) is a statistical technique where the goal is to represent a set of random variables as a linear transformation of statistically independent component variables. The curve let transform as a multiscale transform has directional parameters...

In this paper, the problem of de-noising of an image contaminated with Additive White Gaussian Noise (AWGN) is studied. This subject is an open problem in signal processing for more than 50 years. Local methods suggested in recent years, have obtained better results than global methods. However by more intelligent training in such a way that first, important data is more effective for training,...

To overcome the shortcomings such as significantly de-noising effect and easily losing the details of the image characteristics of the existing image de-noising methods, an image de-noising algorithm based on the hybrid wavelet transform was proposed. The algorithm integrated the advantages of wavelet de-noising retaining image details features and Wiener filter obtaining the optimal solution, ...