ID 原文 译文
11244 现有航迹聚类算法所采用的航迹点对选取方式,无法实现所选航迹点对在空间上的对应,严重影响聚类效果。 ‭Existing track clustering algorithm adopted by the track point to choose way, cannot achieve the selected track is point to the corresponding on the space, seriously affect the clustering effect.
11245 针对这一问题,提出一种基于航迹点法向距离的航迹聚类模型。 ‭In order to solve this problem, this paper puts forward a point method based on track to track distance clustering model.
11246 该模型采用航迹点法向距离作为航迹相似性度量方法,有效地解决了因飞机速度差异引起的航迹点对选取不匹配问题。 ‭The model adopts the track is point to the distance as the track is similarity measure method, can effectively solve the caused by different aircraft speed track point to select mismatches.
11247 通过K-medoids聚类算法对航迹进行二维和三维聚类,使用Davies Bouldin(DB)指标、Dunn指标对聚类结果进行评价。 ‭Through the K - medoids clustering algorithm for 2 d and 3 d track clustering, using Davies Bouldin (DB) index, Dunn index to evaluate the clustering results.
11248 实验表明,提出的模型能够更好地度量航迹之间的相似性,航迹聚类效果更好,从而验证了该模型的合理性和有效性。 ‭Experimental results show that the proposed model can better measure of the similarity between track, track clustering effect is better, so as to verify the rationality and validity of the model. ‭
11249 提出了一种新的变步长算法,并将该算法用于水声信道均衡。 A new variable step size algorithm is proposed, and the algorithm is used for underwater acoustic channel equalization.
11250 该算法克服改进归一化最小均方(developed normanized least mean square,XENLMS)算法依赖固定能量参数λ的局限性,遵循变步长算法的步长调整原则在XENLMS算法的基础上引入一个自适应混合能量参数λk,改善算法收敛速度和鲁棒性。 The algorithm to overcome the improved normalized least mean square (developed normanized further mean square, XENLMS) algorithm is dependent on the limitations of fixed energy parameters lambda, follow the principle of variable step algorithm step length adjustment in XENLMS algorithm on the basis of introducing an adaptive hybrid energy parameters lambda k, to improve the algorithm convergence speed and robustness.
11251 首先通过仿真分析变步长算法中的3个固定参数α,β,μ的取值范围及对算法收敛性能的影响; ‭ First through the simulation analysis of three fixed parameters in variable step size algorithm alpha, beta, the scope of mu and affect the performance of the algorithm convergence;
11252 并在两种典型的水声信道环境下,采用两种调制信号对算法的收敛性能进行计算机仿真。 ‭And in two typical underwater acoustic channel environment, the convergence of the algorithm is using two kinds of modulation signal to computer simulation.
11253 结果显示,新算法的收敛速度明显快于XENLMS算法和已有的变步长算法,收敛性能接近递归最小二乘(recursive least square,RLS)算法的最优性能,但计算复杂度远小于RLS算法。 The results showed that the new algorithm's convergence speed is very fast from XENLMS algorithm and variable step size algorithm, convergence performance is close to the recursive least squares (recursive further square, RLS) algorithm for optimal performance, but computing complexity is far less than RLS algorithm.