ID 原文 译文
19175 此外，考虑到实际雷达工作中存在岛礁、渔船等造成的功率异常大的野点样本时，不同于传统的矩估计、最大似然(ML)估计等方法，组合双分位点估计方法仍可保持估计性能的鲁棒性。 Besides, the CBiP estimator can maintain the robustness of estimation performance when outliers with extremely large power are existing in samples, while other estimators, including moment-based and Maximum Likelihood (ML) estimators, degrade extremely in estimation accuracy.
19176 仿真及实测数据实验表明，在纯杂波环境中，组合双分位点估计方法可以实现与最大似然估计方法近似的估计精度，若存在异常样本，组合双分位点估计方法的估计性能优于上述几种传统估计方法。 Without outliers in samples, the combined bipercentile estimator shows similar accuracy with the ML estimator. With outliers, the combined percentile estimator is the only method with robustness in performance, compared with other estimators afore mentioned.
19177 机器对机器(M2M)通信和设备到设备(D2D)通信都是5G中的关键技术。 Machine-to-Machine (M2M) and Device-to-Device (D2D) communications are both key technologiesin the Fifth Generation (5G) mobile communication systems.
19178 而M2M通信特别需要考虑提高设备的能量效率(EE)以延长设备的生存周期。 In M2M communications, the Energy Efficiency(EE) especially needs to be improved to extend the life cycle of the M2M equipment.
19179 该文将M2M技术与D2D技术相结合，考虑M2M设备使用D2D技术进行通信，同时M2M设备复用蜂窝网络中的人对人(H2H)通信的频谱资源。 In this paper, the M2Mand D2D technologies are combined and the D2D technology is used to realize M2M transmission. At the same time, M2M users are allowed to reuse spectrum resources with Human-to-Human (H2H) devices in the cellular networks.
19180 为了同时保证两种系统的服务质量(QoS)需求，建立了最大化M2M的能量效率，最大化H2H系统容量和，以及最小化M2M系统对H2H系统干扰的多目标优化问题(MOOP)。 To guarantee the Quality of Service (QoS) of these two systems simultaneously, a Multi-Objective Optimization Problem (MOOP) is then formulated to maximize the sum throughput of H2H systems, and the sum EE of M2M systems and to minimize the interference from M2M communications to H2H networks.
19181 为了解决该问题，采用惩罚函数的方法将二进制变量松弛约束，进而采用凹凸过程(CCCP)方法将非凸的单目标优化问题转化为凸优化问题，并最终通过加权切比雪夫算法得到原多目标优化问题的Pareto最优解。 To solve this MOOP, the penalty function method is firstly adopted to relax the original binary variables, and then the ConCave-Convex Procedure (CCCP) method is used to convert the non-convex single-objective problems into convex problems. Finally, the weighted Tchebyshev algorithm is utilized to obtain the Pareto solution ofthe original MOOP.
19182 通过与传统的加权和算法进行比较，仿真结果证明了该算法的有效性。 By comparing with the traditional weighted sum method, the effectiveness of the proposed method is proved by simulation results.
19183 针对传统无线传感网络(WSN)中资源部署与特定任务的耦合关系密切，造成较低的资源利用率，进而给资源提供者带来较低的收益问题， The close relationship between resource deployment and specific tasks in traditional Wireless SensorNetwork(WSN) leads to low resource utilization and revenue.
19184 根据虚拟传感网络请求(VSNR)的动态变化情况，该文提出虚拟传感网络(VSN)中基于半马尔科夫决策过程(SMDP)的资源分配策略。 According to the dynamic changes of Virtual Sensor Network Request(VSNR), the resource allocation strategy based on Semi-Markov Decision Process(SMDP) is proposed in Virtual Sensor Network(VSN).