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This paper develops an inertial-sensing-based wearable human activity classification system and its associated human activity classification algorithm for accurately recognizing human daily activity. The proposed system used two inertial sensing modules, which are worn on subjects' wrist and ankle, to collect motion signals of human activities, and utilized the nonparametric weighted feature extraction...
In today's internet era, people are facing huge amount of information, that is the so called information overloading. It has hampered people to make full use the convenience of the Internet. There are several ways to solve the problem, such as category list, search engine and re-commendation engine. Among them search engine and recommendation engine are more popular. In real situation a recommendation...
This paper introduces an improved de-noising SOBI (Second Order Blind Identification) separation method, which is used to separate mixed components of different composite materials damage acoustic emission simulated signals. The contrastive analysis and numerical simulations of a variety of blind source separation algorithms are investigated, which suggests that traditional SOBI performance degrades...
The paper puts forward a new classification method of association rules that is based on support-significant structure. Starting from the characteristics of customer segmentation, this method introduces a up-to-date rule evaluation index significance during the produce process of classification rules, therefore, the evaluation and selection of principle have serious statistical basis. After simple...
The suitability of catenary directly affects the performance of current collecting between the pantogragh and catenary, in a general way whether the catenary has large unsuitability, namely hard spot, is depended on which if the maximum associated with the vertical impact acceleration of pan-head within each segment is larger than a given threshold, it will be calculated by fuzzy c-mean algorithm...
In this paper, we propose a fuzzy clustering decision tree (FCDT) for the classification problem with large number of classes and continuous attributes. A hierarchical clustering concept is introduced to achieve a finer fuzzy partition. The proposed clustering algorithm split the data set into leaf clusters using splitting attributes based on a separation matrix and fuzzy rules. The leaf clusters...
It built a classifier, which could improve recognition rate of image feature. Based on statistical learning theory, it built a classifier on Support Vector Machine(SVM), and determined the parameter of SVM and Guass radial kernel function. In the experiment, classifier of SVM was trained by feature sample, then carried on classifying , recognition and detection. The result of simulation showed that...
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