There exists a number of cepstral de-noising algorithms which perform quite well when trained and tested under similar acoustic environments, but degrade quickly under mismatched conditions. We present two key results that make these algorithms practical in real noise environments, with the ability to adapt to different acoustic environments over time. First, we show that it is possible to leve...

We have developed a method focusing on ECG signal de-noising using Independent component analysis (ICA). This approach combines JADE source separation and binary decision tree for identification and subsequent ECG noise removal. In order to to test the efficiency of this method comparison to standard filtering a wavelet- based de-noising method was used. Freely data available at Physionet medic...

An interactive mathematical methodology for time series prediction that integrates wavelet de-noising and decomposition with an Artificial Neural Network (ANN) method is put forward here. In this methodology, the underlying time series is initially decomposed into trend and noise components by a wavelet de-noising method. Both trend and noise components are then further decomposed by a wavelet ...

In image processing, image is corrupted by different type of noises. But generally medical image is corrupted by speckle noise. So image de-noising has become a very essential exercise all through the diagnose. Noises are of two type additive and multiplicative noise. Speckle noise is multiplicative noise, so it’s difficult to remove the multiplicative noise as compared to additive noise. The t...

De-noising of speech signal polluted by background noise, which is of great practical significance for effective transmission and accurate recognition of sound, is important. Local characteristic-scale decomposition is introduced, and it can divide the speech into lowand high-frequency parts without a loss in useful speech. The algorithm accelerates the speed of convergence, as well as pretreat...

Noise has great influence on the signal analysis for centrifugal compressor. In order to eliminate the noise, the iterative singular value decomposition (ISVD) de-noising is applied in this paper. Firstly, the algorithm of this method is introduced. It is based on singular value decomposition about the trajectory matrix of attractor which is reconstructed according to time delay embedding theor...

432 www.scientistlink.com Abstract: A physiological signal monitoring system and alerting system using wireless technology is presented. The two types of physiological signal monitoring are captured from the body through leads and using the radio-frequency transmitting and receiving module the data are interfaced to computer systems. Furthering using a developed user interface module the captur...

Abstract–Planetary gearbox is widely used in many fields due to its robustness and high power-weight ratio, but implementation of fault diagnosis on it is challenging. This paper proposes a new fault diagnosis method for planetary gearbox based on empirical mode decomposition (EMD) and adaptive multi-scale morphological gradient filter (AMMGF). The proposed method has two dominant strengths: it...

In allusion to the losses of image detail and texture structure information during image de-noising process, an image de-noising algorithm based on non-related dictionary learning is proposed in this paper. Firstly, this algorithm is adopted to obtain selfadaption redundant dictionary for the noisy image through the dictionary learning algorithm; secondly, HOG features and gray-level statistica...

The precision agriculture decision-making needs of geographic information visualization analysis for farmland. In order to get 3D visualization of farmland, the Matlab software and wavelet transform were used for 3Dterrain survey data processing. Haar, DB6, Sym8, coif3 wavelet were used on the 3 layer decomposition of elevation data de-noising test, DB6 wavelet was used on the two to seven laye...