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中文摘要：
针对在有高斯量测噪声和杂波环境下的数据关联问题,提出了一种基于残差三阶累积量的跟踪门算法,通过对残差数据累计序列的三阶累积量的计算,抑制了高斯噪声对跟踪门的影响,且有效地排除了杂波的干扰,从根本上提高了跟踪门的性能.仿真实验结果验证了该算法的有效性和稳健性.
英文摘要：
Aiming at the data association problem in the Gaussian noise and clutter environment, a track- ing gate algorithm based on the residual third-order cumulants is proposed, which suppresses the effect of Gaussian noise on the tracking gate, effectively rules out the clutter interference and fundamentally improves the performance of the tracking gate by adopting the third-order cumulants computation basing on the cumulative residual data sequence. Finally, the feasibility and effectiveness of this algorithm has been fully verified by its simulation results.
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同项目期刊论文
Stability analysis for the generalized Hopfield neural networks with multi-level activation function
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