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A Fast Data Fusion Algorithm Based on Matrix Analysis for Target Recognition in Sensor Networks

机译:基于矩阵分析的传感器网络目标识别快速数据融合算法

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Data fusion always be used to solve the problem of target recognition in wireless sensor networks, and Dempster-Shafer inference have been proven one of effective methods. However, the high computation complexity of D-S evidence combination usually prevent it to be used in low ability sensor networks directly, especially it may violate the requirements for real-time processing and synchronization of sensor networks. To increase the speed of target recognition in wireless sensor networks, a fast data fusion algorithm based on matrix analysis is proposed in this paper, which inherits the idea of D-S evidence theory. The algorithm holds the same recognition capability as D-S evidence combination formula, but reduces time complexity. This conclusion has been confirmed by simulation.
机译:数据融合一直被用来解决无线传感器网络中目标识别的问题,而Dempster-Shafer推理已被证明是一种有效的方法。然而,D-S证据组合的高计算复杂度通常会阻止其直接用于低能力传感器网络,尤其是它可能违反了传感器网络实时处理和同步的要求。为了提高无线传感器网络中目标识别的速度,本文提出了一种基于矩阵分析的快速数据融合算法,该算法继承了D-S证据理论的思想。该算法具有与D-S证据组合公式相同的识别能力,但降低了时间复杂度。该结论已通过仿真得到证实。

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