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Functional near-infrared spectroscopy (fNIRS) can be employed to investigate brain activation by measuring the absorption of near-infrared light through an intact skull. fNIRS can measure hemoglobin signals, which are similar to functional magnetic resonance imaging (fMRI) blood-oxygen-level-dependent (BOLD) signals. The general linear model (GLM), which is a standard method for fMRI imaging, has...
It has been found that stochastic resonance can filter out the image noise and enhance the image. However, since the stochastic resonance has a characteristic that the high frequency energy is shifted to the low frequency, the denoised image will lose detail and become blurred. Because the noise and detail of the image are mainly distributed in the high frequency band, image denoising and detail retention...
The objective of this work is to detect delay times between two ultrasonic signals, one of them considered as a reference and the other signal as the signal to be evaluated, using the wavelet transform, to indirectly estimate temperature changes. In this work the evaluation of 3 types of wavelets (Morlet, Mexican Hat and Daubechies 5) was made to detect the delay time in echo ultrasonic signals which...
The main purposes of this paper are to achieve human face detection and head posture recognition, as well as to track a dynamic image in real time via camera. First, skin-color region is detected. After morphological operations, unnecessary noise is removed, and the method of seed region growing is used to mark pixel blocks. Then the skin-color region is determined whether or not each block is a human...
Recently, with the obvious increasing number of cardiovascular disease, the automatic classification research of Electrocardiogram signals (ECG) has been playing a significantly important part in the clinical diagnosis of cardiovascular disease. In this paper, a 1D convolution neural network (CNN) based method is proposed to classify ECG signals. The proposed CNN model consists of five layers in addition...
In this paper, a combining Electroencephalographic (EEG) and Electro-oculographic (EOG) approach has been developed in order to allow the control of the displacement of a wheelchair by disable peoples. NeuroSky MindeWave headset and wet superficial electrodes have been used for the measurement of EEG and EOG signals respectively. These signals have been processed using Wavelet Transform (WT) and Principal...
Vibration monitoring and analysis is a powerful and recommended tool for preventive maintenance and early detection of impending failures in rotary machine. The demand for cost efficient, reliable and safe rotating machinery requires accurate fault diagnosis, classification and prognosis systems. This work presents a study to explore the performances of bearing fault diagnosis by using wavelet neural...
Ultrasonic backscatteredsignals contain information regarding the scatterer structures of the imaged biological tissues; a uniform scatterer distribution could be represented by periodicities in the backscattered signals. This work aims to characterize these scatterer periodicities using wavelet improved cepstral analysis. This technique was tested on simulated ultrasound signals, where the periodicity...
With the intelligentization of distribution network, a large scale of power electronic devices are applied in energy conversion. And the system flow of distribution network becomes random and varies greatly, which puts forward higher requirements for measurement and protection. Therefore, it's necessary to detect and identify short-circuit fault rapidly and effectively. In this paper, an early detecting...
The Noise reduction techniques with wavelet transform are widely used in non-destructive testing and evaluation (NDT&E). In this paper, a new non-destructive testing method referred to as magneto-acousto-electrical NDT was proposed. At the same time, based on fully taking into account the signal features we employ analytic wavelet thresholding method to improve the de-noising performance. The...
Series arc fault is an important incentive for electrical fires. Wavelet transform is a widely used series arc fault identification method. However, it is difficult to distinguish the normal condition and arc fault when only using wavelet transform, and a large amount of redundant data will be generated. To solve this problem, this paper presents a new series arc fault identification method which...
Objective: In this study, we attempted to develop an accurate and effective rhythm analysis tool which gives spectrum of Transcranial magnetic stimulation (TMS) evoked Electroencephalography (EEG) oscillation with both high resolution in time and frequency domain for understanding the TMS induced EEG and relative neural mechanisms. Methods: We investigated the possibility of applying the synchrosqueezing...
An algorithm for detecting and extracting crack defects in glassware using wavelet transform is proposed in this paper. Firstly, the canny image segmentation and the local adaptive dynamic threshold segmentation are carried out on the glassware image with unobvious crack defects. Then, the wavelet decomposition is applied separately on the segmented images. And finally the wavelet fusion is used to...
Aiming at the non-ideal recognition rate caused by single gait feature in the process of gait recognition, in order to further improve the accuracy of gait recognition, this paper proposes a gait recognition method based on object contour feature fusion. The method firstly extracts the distance from centroid to the key points in the contour image, the width feature and the low frequency statistical...
Terahertz radar coded-aperture imaging technology can achieve high-resolution, forward-looking and staring imaging by producing spatiotemporal independent signals in the imaging area. Sparse reconstruction algorithm is efficient in the point target imaging, whereas it becomes invalid for complex area targets. This paper proposes a method combining wavelet transform and orthogonal matching pursuit...
The paper presents the results of modeling adaptive decomposition for ultra-high definition television, which provides image compression without subjective deterioration of quality. The decomposition of the images was carried out in the spectral region for the cases of wavelet analysis and Fourier transformation, depending on the signal-to-noise ratio at the image edges. Quantitative estimates of...
In this paper the problem of improving the reliability of nonlinear dynamic objects fault diagnosing is presented. Model-based diagnostics nonparametric identification method is used. Diagnostic models are constructed on the base of Volterra kernels wavelet transforms. The effectiveness of the suggested diagnostic models based on Volterra kernels wavelet transforms is analyzed on the basis of simulation...
Mobile communication has become an important part of our daily lives for voice communication and data sharing and access over the Internet. Mobile communication is an open network, so maintaining the privacy and reliability of data has always been anxiety. The reliability of the data against channel noise can be achieved by various error correction codes. The purpose of the channel coding process...
The problem of adaptive reduction of noise of phonocardiograms (PCG) The problem of adaptive reduction of noise of phonocardiograms (PCG) based on wavelet transformation is considered in the article. Adaptive noise reduction is realized on the basis of the wavelet decomposition of the PCG using the Daubechies 4 wavelet function. The Daubechy 4 wavelet function is identical to the PCG patterns and...
Aiming at the problem of blocked pipe in coal slurry pipeline transportation process, in the two phase of the project of 50MW unit in Shanxi Huangling coal gangue power generation company, the method of pressure wave slime pipeline blockage location is proposed based on wavelet transform, which is the analysis of the pipeline positioning principle based on the pressure wave method, the pressure wave...
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