An accelerated singular value thresholding (SVT) algorithm was introduced for matrix completion in a recent paper [1], which applies an adaptive line search scheme and improves the convergence rate from O(1/N) for SVT...An accelerated singular value thresholding (SVT) algorithm was introduced for matrix completion in a recent paper [1], which applies an adaptive line search scheme and improves the convergence rate from O(1/N) for SVT to O(1/N2), where N is the number of iterations. In this paper, we show that it is the same as the Nemirovski’s approach, and then modify it to obtain an accelerate Nemirovski’s technique and prove the convergence. Our preliminary computational results are very favorable.展开更多
正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)中至关重要的一项技术是信道估计,本文提出一种基于矩阵恢复的OFDM信道估计方法,将连续多个OFDM信号的频域信道构造成一个信道矩阵,由于这个信道矩阵是低秩的,所以可以...正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)中至关重要的一项技术是信道估计,本文提出一种基于矩阵恢复的OFDM信道估计方法,将连续多个OFDM信号的频域信道构造成一个信道矩阵,由于这个信道矩阵是低秩的,所以可以将信道估计问题转换为信道矩阵的加权截断核范数最小化问题,并使用改进的奇异值阈值(Singular Value Thresholding,SVT)算法对信道矩阵进行恢复。仿真结果表明,本文提出的方法和传统信道估计算法相比,使用相同导频数可以获得更高的估计精度,在获得相同估计精度时,消耗导频数更少。与基于压缩感知的信道估计方法相比,本文方法消耗相同数量的导频,但可直接获得高精度的OFDM信道的频域估计。展开更多
为了降低联合概率数据关联(joint probabilispic data association,JPDA)算法的计算复杂度,解决跟踪临近目标时出现的航迹合并问题,基于量测自适应消除方法,提出了一种改进JPDA算法.该算法首先通过Cheap JPDA算法计算互联概率,降低算法...为了降低联合概率数据关联(joint probabilispic data association,JPDA)算法的计算复杂度,解决跟踪临近目标时出现的航迹合并问题,基于量测自适应消除方法,提出了一种改进JPDA算法.该算法首先通过Cheap JPDA算法计算互联概率,降低算法计算量;其次对聚概率矩阵加以阈值处理,通过重建确认矩阵,进一步优化算法复杂度;最后采用自适应消除方法,去掉聚概率矩阵中易引起错误关联的量测,减小JPDA算法在关联临近目标时的误差.仿真实验结果表明:相较于JPDA算法及Scaled JPDA(SJPDA)算法,本文算法在保证跟踪精度的前提下,降低了算法复杂度,提高了时效性;在跟踪临近目标及交叉目标时,改进算法能避免航迹合并现象及跟错目标情况的发生.展开更多
文摘An accelerated singular value thresholding (SVT) algorithm was introduced for matrix completion in a recent paper [1], which applies an adaptive line search scheme and improves the convergence rate from O(1/N) for SVT to O(1/N2), where N is the number of iterations. In this paper, we show that it is the same as the Nemirovski’s approach, and then modify it to obtain an accelerate Nemirovski’s technique and prove the convergence. Our preliminary computational results are very favorable.
文摘正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)中至关重要的一项技术是信道估计,本文提出一种基于矩阵恢复的OFDM信道估计方法,将连续多个OFDM信号的频域信道构造成一个信道矩阵,由于这个信道矩阵是低秩的,所以可以将信道估计问题转换为信道矩阵的加权截断核范数最小化问题,并使用改进的奇异值阈值(Singular Value Thresholding,SVT)算法对信道矩阵进行恢复。仿真结果表明,本文提出的方法和传统信道估计算法相比,使用相同导频数可以获得更高的估计精度,在获得相同估计精度时,消耗导频数更少。与基于压缩感知的信道估计方法相比,本文方法消耗相同数量的导频,但可直接获得高精度的OFDM信道的频域估计。