ID	原文	译文
2943	首先，为节点定义局部信息度量指标———社团连接度和邻居连接度，建模节点与社团的关系，缩小了计算范围;	Firstly, we introduce two local information metrics for each net-work node—community connectivity score and neighborhood connectivity score, to model the relationship between nodesand communities;
2944	然后，每次并行地迭代执行缩减、扩展、去重等操作，并更新局部度量指标，通过松弛每次迭代的终止条件，发现近似最优社团集合而不是最优社团，最终算法复杂度为 O(m + n)。	secondly, based on local metrics, we can concurrently execute the iterations of reduction, expansion, and duplication removal to find the approximately optimal communities instead of the optimal community, and achieve a low complexity O(m + n).
2945	基于真实的大规模社交网络数据的试验分析表明:与当前流行的重叠社团挖掘算法相比，Li-FOCD 在不损失检测质量的前提下，大幅提升了计算效率。	Experimental analysis based on real large-scale social networking datasets shows that our algorithm outperforms some popular overlapped community finding algorithms in terms of computational time while not compromising with quality.
2946	非线性系统估计的过程是一个多传感器信息融合的过程，在集中处理量测数据的过程中，Kalman 滤波具有很高的计算复杂度。	The estimation process of nonlinear system is a process of multi-sensor information fusion. During theprocess of data processing, Kalman filter has high computational complexity.
2947	尤其当系统模型中存在随机偏差时，扩维后计算量大幅增大，容易造成系统溢出和运行失败的问题。	Especially when there are random deviations inthe system model, the amount of calculation increases greatly after dimension expansion, which is easy to cause system over-flow and operation failure.
2948	通过将两阶段容积 Kalman 滤波嵌入到扩展信息滤波框架的方式，提出了一种两阶段高维容积信息滤波算法。	During the process of data processing, Kalman filter has high computational complexity. By embedded the two-stage Cubature Kalman filter into the extended information filtering frame-work, Two-stage High degree Cubature Information Filter(TSHCIF)is proposed.
2949	该算法初始化容易，计算量较小，直接利用协方差矩阵的逆与信息矩阵之间的等价关系参与滤波递推的过程，减少了对滤波增益阵的计算。	The algorithm is easy to initialization andsmall in computation. It takes advantage of the equivalence relation between the inverse of covariance matrix and information matrix to participate in the process of filter recurrence, and reduces the computation of filter gain matrix.
2950	在协方差矩阵的解算过程中，两阶段算法的协方差矩阵之间存在有耦合关系，	In the solution of the covariance matrix, there is a coupling relationship in the covariance matrices of the two-stage algorithm.
2951	因此在信息滤波中，两阶段信息矩阵之间也存在着某种耦合关系，算法中通过将非线性 T 变换和矩阵求逆应用于信息矩阵，得到了两阶段信息矩阵与协方差矩阵之间的耦合关系。	Therefore, thereis a coupling relationship between the two stage information matrix. In the algorithm, the nonlinear T transformation and theinverse of the matrix should be applied to the information matrix. The coupling relationship between the two-stage informa-tion matrix and the covariance matrix is obtained.
2952	通过纯方位跟踪系统的仿真实验，验证了两阶段高维容积信息滤波算法在精度上高于容积 Kalman 滤波算法，在运行时间上也短于容积 Kalman 滤波算法，证明了该算法的可用性。	Through the simulation experiment of bearings only tracking system, it is verified that TSHCIF is superior to CKF in accuracy, and the running time is also shorter than CKF, which proves the availa-bility of the algorithm.