An improved localization algorithm was proposed to solve the problem of low location accuracy and large computational cost in nearest neighbor(KNN) algorithm for LANDMARC system. The novel algorithm combined RFID and ...
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An improved localization algorithm was proposed to solve the problem of low location accuracy and large computational cost in nearest neighbor(KNN) algorithm for LANDMARC system. The novel algorithm combined RFID and wireless sensor networks. It divided location area into several sub areas, utilized the sensor network to locate the target node to corresponding sub area, removed the reference nodes far from the target node, narrowed down the selection scope of the k value, used KNN algorithm to calculate the coordinate of target node in the sub area and applied the Taylor series iteration to improve the accuracy. Experiment results shows that the proposed algorithm improves the location accuracy evidently.
In the Brain-computer interface, classification and recognition technology plays an important role, especially the EEG classification and recognition for the movement imagery. In this paper, we use a new type of senso...
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This paper presents a novel human-machine interface to control an intelligent wheelchair based on surface electromyography (sEMG) signals. Forehead sEMG signals generated by the facial movements are obtained and analy...
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In the Brain-computer interface, classification and recognition technology plays an important role, especially the EEG classification and recognition for the movement imagery. In this paper, we use a new type of senso...
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In the Brain-computer interface, classification and recognition technology plays an important role, especially the EEG classification and recognition for the movement imagery. In this paper, we use a new type of sensors to collect EEG signals. According to imagine the movement of left or right hand to identify two types of thinking, we proposed a new recognition method based on AR(auto-regressive) and SVM (support vector machine). In the identification process uses different kernel functions to classify comparison test. Compared to the traditional method based on support vector machine and Bayes, the correct rate has been greatly improved, and verifies the effectiveness of the method.
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