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Based on the characteristics of the pulse singularity signals, a new method for detecting the pulse singularity signals is proposed using the Bernoulli probability to describe singularity points. The proposed method converts the detection problem to a parameter estimation problem and solves it using a maximum likelihood method. The experimental results show that the proposed method identifies pulse...
This study proposed to use wavelet transfer to acquire image features, and use back-propagation neural network to classify type of textile texture. Firstly, wavelet transfer is applied to obtain vertical, horizontal and diagonal images of original image, and compute its wavelet energy to take them as texture features of this image. Finally, the back-propagation neural network is adopted to recognize...
Fabric defect detection and classification plays a very important role for the automatic detection in fabrics. This study refers to the four common seen defects of stretch knitted fabrics: laddering, end-out, hole, and oil spot. First of all, wavelet transfer is applied to obtain its wavelet energy to take them as defect features of this image, and then the back-propagation neural network (BPNN) was...
Wavelet thresholding method based on wavelet transform (WT) is a de-noising method to eliminate the Gaussian white noise. And the wavelet decomposing scale is one of the main factors to influence the de-noised result of this method. In this paper, a new algorithm based on 3sigma criterion is presented to calculate the optimal wavelet decomposing scale. Furthermore, it is used to de-noise electrocardiogram...
This study proposed to use wavelet transfer to acquire image hue and value as image features, and use Back-propagation Neural Network Fuzzy Clustering analysis to recognize type of textile texture. Firstly, the RGB color space of original color image is transferred to HSV color space; secondly, wavelet transfer is applied to obtain vertical, horizontal and diagonal images of hue and value, and compute...
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