ID 原文 译文
16945 随后，给出了距离相关噪声AOA定位下广义克劳美罗下界(GCRLB)。 The Generalized Cramer-RaoLower Bound (GCRLB) of AOA localization is calculated.
16946 在此基础上理论分析了无约束最优传感器位置分布和约束条件下最优传感器位置分布。 Further, the unconstrained optimal sensor placementand constrained optimal sensor placement are theoretically analyzed.
16947 以GCRLB的迹最小化为目标函数建立AOA协同定位下多无人机路径规划问题，采用罚函数和LM算法优化求解，仿真验证了所提算法的有效性。 Then a path planning model for UAVs is constructed with minimizing the trace of GCRLB, which is solved optimally with penalty function and LM (Levenberg-Marquardt) algorithm. The effectiveness of the proposed algorithm is illustrated with simulation results.
16948 针对网络流量分类过程中出现的类不平衡问题，该文提出一种基于加权对称不确定性(WSU)和近似马尔科夫毯(AMB)的特征选择算法。 Class imbalance always exists in the process of network traffic classification. Considering the problem, a new feature selection algorithm using Weighted Symmetric Uncertainty (WSU) and Approximate Markov Blanket (AMB) is proposed.
16949 首先，根据类别分布信息，定义了偏向于小类别的特征度量，使得与小类别具有强相关性的特征更容易被选择出来； Firstly, a feature metric is defined using category distribution information, whichis biased to minority classes. This makes it easier pick out features which have strong correlation with minorityclasses.
16950 其次，充分考虑特征与类别间、特征与特征之间的相关性，利用加权对称不确定性和近似马尔科夫毯删除不相关特征及冗余特征； Then, considering the correlation between features and categories and between features and features,the weighted symmetry uncertainty and approximate Markov blanket are used to delete the unrelated featuresand redundant features.
16951 最后，利用基于相关性度量的特征评估函数以及序列搜索算法进一步降低特征维数，确定最优特征子集。 Finally, the feature dimension is further reduced to determine the optimal featuresubset, by using feature evaluation functions based on correlation measures and sequence search algorithms.
16952 实验表明，在保证算法整体分类精确率的前提下，算法能够有效提高小类别的分类性能。 The experimental results demonstrate that the algorithm can effectively improve the classification performanceof minority classes without sacrificing the accuracy of the overall classification.
16953 该文研究了多小区混合非正交多址接入(MC-hybrid NOMA)网络的资源分配。 Resource allocation in Multi-Cell hybrid Non-Orthogonal Multiple Access-orthogonal multiple access(MC-hybrid NOMA) networks is studied in this paper.
16954 为满足异构用户的服务体验，以最大化全网综合平均意见评分(MOS)累加和为目标，考虑基站选择、信道接入和功率资源分配的联合优化问题，该文提出一种用户、基站和信道3方的2阶段转移匹配算法，并根据用户MOS进行子信道功率优化。 To satisfy the Quality of Experience (QoE) of differentservice types of users, an algorithm joint user-BS association, sub-channel assignment and power allocation isproposed to maximize the sum Mean Opinion Scores (MOSs) of users in the networks. A low-complexity two-step approach based on matching game theory and developed power allocation strategy based on QoEproportional fairness are proposed.