Lianmeng Jiao

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The combination of sources of evidence with reliability has been widely studied within the framework of Dempster-Shafer theory (DST), which has been employed as a major method for integrating multiple sources of evidence with uncertainty. By the fact that sources of evidence may also be different in importance, for example in multi-attribute decision making(More)
The performance of the nearest-neighbor (NN) classifier is known to be very sensitive to the distance metric used in classifying a query pattern, especially in scarce-prototype cases. In this paper, a pairwise-weighted (PW) distance metric related to pairs of class labels is proposed. Compared with the existing distance metrics, it provides more flexibility(More)
For nonlinear systems, Converted Measurement Kalman filter as one of various modifications of the Kalman filter can be used to estimate the state with the non-linear measuring equations, effectively. Although the Converted Measurement Kalman filter is powerful tools for nonlinear state estimation, we might have information about a system that the Converted(More)
The three-dimensional CMKF-U with only position measurements is extended to solve the nonlinear tracking problem with range-rate measurements in this paper. A pseudo measurement is constructed by the product of range and rangerate measurements to reduce the high nonlinearity of the rangerate measurements with respect to the target state; then the mean and(More)
The evidential K-nearest neighbor (EK-NN) method, which extends the classical K-nearest neighbour (K-NN) rule within the framework of evidence theory, has achieved wide applications in pattern classification for its better performance. In EK-NN, the similarity of test samples with the stored training ones are assessed via the Euclidean distance function,(More)