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  • 1
    Publication Date: 2015-05-19
    Description: This paper presents a novel flexible tactile sensor structure and proposes an efficient decoupling algorithm for the tactile sensor. Firstly, structure of the sensor model is introduced, and the sensing mechanism of the sensor array based on force-sensitive conductive rubber is analyzed. Then the mapping relation between the resistances of conductive pillars and the three-dimensional force is deduced. After that, the force applied on the tactile sensor is decoupled from the resistance information by the improved Back Propagation Neural Network (BPNN) algorithm with the number of hidden layer nodes optimized. The flexible tactile sensor model achieves the decomposition of the three-dimensional information from the structure with its unique design, avoids the direct interference between electrodes of the sensor array, reduces the structural complexity and the nonlinear degree, improves the decoupling accuracy, and accelerates the decoupling rate.
    Print ISSN: 1687-725X
    Electronic ISSN: 1687-7268
    Topics: Electrical Engineering, Measurement and Control Technology
    Published by Hindawi
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  • 2
    Publication Date: 2009-01-01
    Description: Signals in data are often detected by analyzing anomaly field that is calculated by subtracting the mean value over a time length from the data. Here we demonstrate that the anomaly calculation removes signals which satisfy that the ratio between the time length of the mean T and signals' period L is an integer (i.e., T/L=n where n is an integer) and retains other signals if the ratio is not an integer. In climatic and other studies, the time length of the mean is usually chosen as T=12 months from January to December and the mean is called the monthly climatology. Anomaly is calculated by subtracting the monthly climatology from data. This anomaly calculation thus removes the climatic signals with the periods of 12, 6, 4, 3, 2.4, and 2 months which correspond to (12 months)/n with n=1, 2, 3, 4, 5, and 6, respectively, whereas it retains other signals such as those with the periods of 11, 10, 9, 8, 7, and 5 months. This paper suggests that one should be cautious when an anomaly field is used in research. The conventional notion is that the monthly anomaly calculation removes the annual cycle. However, here we show that the anomaly calculation removes all signals as long as the time length of the mean is an integer multiple of signals' period.
    Print ISSN: 1687-9406
    Electronic ISSN: 1687-9414
    Topics: Geosciences
    Published by Hindawi
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