De-noising algorithms based on wavelet thresholding replace small wavelet coeecients by zero and keep or shrink the coeecients with absolute value above the threshold. The optimal threshold minimizes the error of the result as compared to the unknown, exact data. To estimate this optimal threshold, we use Generalized Cross Validation. This procedure is fast and does not require an estimation fo...

The use of electrocardiogram (ECG) plays significant role in the diagnosis of heart disease and human computer interface etc. But, the ECG signals get affected from different types of noise during data acquisition due to which it faces the problem to detect actual abnormality. De-noising of the ECG signal is so indispensable and for de-noising it various researcher work in this area. In this wo...

129 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...

Fourier transform is applied to detect the direction of stripe noise before de-noising, which is advantageous for selecting the corresponding detail coefficients for threshold quantization after stationary wavelet transform. Depending on the direction of stripe noise, the corresponding detail coefficients contain stripe noise need to be removed, while retaining the approximate coefficients and ...

Partial discharge (PD) activity measurements have been carried out by selecting noise signals (de-noising) using Support Vector Machine (SVM)and then recognized Convolutional Neural Network (CNN). CNN testing was various models such as activation methods: Sigmoid, Softmax, Relu, Tanh, Swish. Number of layers used is 1, 2, 3, 4 with filter sizes 32, 64, 128, 256 and kernel 3x3, 2x2, 1x1, 1x2, 1x...

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...

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...

Images are susceptible to various kinds of noises, which corrupt the pictorial information stored in images. Image de-noising has become an integral part image processing workflow. It is used attenuate noises and accentuate specific within. Machine learning important tool image-de-noising workflow terms its robustness, accuracy, time requirement. This paper explores numerous state-of-the-art ma...

With the increasing demands of precise positioning in weak signal environment, high sensitive GNSS receiver research and development has been pushed badly in need. Conventional GNSS signal acquisition techniques are considered inadequate when the incoming signal is too weak. In this paper we have mainly consider wavelet denoising algorithm applying in weak GNSS signal acquisition. Conventional ...