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In this paper, an interacting multiple model algorithm is proposed to estimate the motion state of a target. The motion state of a target in a certain period is constructed by four basic motion states of uniform linear motion, even accelerating of linear motion, variable speed linear motion and turning motion. Markov process is used to model the transfer probability of four basic motion states. Kalman filter is used to estimate and update the target's motion state. The simulation results show that the algorithm achieves better rate and smooth position observation of maneuvering targets, and is suitable for moving state estimation of ground maneuvering targets.

Recently, there has been a trend to combine independent component analysis and canonical polyadic decomposition (ICA-CPD) for an enhanced robustness for the computation of CPD, and ICA-CPD could be further converted into CPD of a 5th-order partially symmetric tensor, by calculating the eigenmatrices of the 4th-order cumulant slices of a trilinear mixture. In this study, we propose a new 5th-order CPD algorithm constrained with partial symmetry based on joint diagonalization. As the main steps involved in the proposed algorithm undergo no updating iterations for the loading matrices, it is much faster than the existing algorithm based on alternating least squares and enhanced line search, with competent performances. Simulation results are provided to demonstrate the performance of the proposed algorithm., IEEE China Summit & International Conference on Signal and Information Processing. IEEE, 2014:804 - 808

We present an algorithm for jointly performing canonical polyadic decomposition (J-CPD) upon two tensors with one shared loading matrix. Target tensors are firstly matricized and factorized into two components each, and a joint nonorthogonal joint diagonalization based scheme is performed secondly to restore the joint Khatri-rao structures of the results obtained in the first step. Lastly, estimates of loading matrices could be obtained by singular value decomposition based scheme. The proposed algorithm could be used to extract common structures shared with different tensors, and such problem would occur in applications that involve joint utilization of multiple datasets or multiple statistics such as covariance and pseudo-covariance. Simulations are provided to examine the performance of the proposed algorithm.

Rural regional development disparity has become a major development issue in China. As non-farm income is the main source of farm income and the key to solve regional disparity, our research focuses on farmers' non-farm income. While most existing research focused on micro factors that influence regional development disparity, our research explored macro factors, especially trade openness on non-farm income, using the data of the past twenty years. The study showed that trade openness has exerted positive and significant impact on farmers' non-farm income, and facilitates convergence of regional disparity.

To support the advanced concept technology demonstration of intelligence reconnaissance system application on future information battlefield, multiagent- oriented modeling and simulation technology is applied to set up the mappings from intelligence reconnaissance system’s members to respective agents, by which the distributed multi-agent system is designed. The established distributed multi-agent system model of intelligence reconnaissance can afford advantage for realizing the simulation of the external, dynamic, complicated and intelligent process.