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In order to improve analog circuit recognition, combined KPCA and SVDD, put forward one scheme of analog circuit state recognition based on KPCA-SVDD. Firstly distill characteristic of the outputs voltage signal by KPCA, taking the energy as the eigenvector of state recognition, Then adopt the SVDD categorize method to establish SVDD model of different state, carry on circuit state recognition, Finally...
In this paper, we aim to study and classify gait patterns among flat walking, descending stairs, and ascending stairs using inertial measurement unit (IMU) including triaxial accelerometers and gyroscopes. Six subjects were invited to gather gait data of flat walking, descending stairs, and ascending stairs wearing the shoe-integrated system with free speeds. The design of the classifier for identifying...
In this paper, we propose a coarse-to-fine segmentation method for extracting moving regions from compressed video. First, motion vectors are clustered to provide a coarse segmentation of moving regions at block level. Second, boundaries between moving regions are identified, and finally, a fine segmentation is performed within boundary regions using edge and color information. Experimental results...
Equable principal component analysis (EPCA) is a powerful technique of feature extracting. It can reduce a large set of correlated variables to a smaller number of uncorrelated components. Support vector machines (SVM) is a novel pattern classification approach. It is very efficient in solving clustering problems that are not linearly separable. This paper presents a method of expression recognition...
For more precise control of the FES-derived gait, the timing of specific gait phases is needed. With the information of when the legs are in each phase of gait, the quality of the gait during each phase can be assessed. The goal of this paper is to investigate potential use of machine learning techniques, in particular Support Vector Machine (SVM), and Force Sensitive Resistor (FSR) to detect discrete...
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