ID 原文 译文
17615 仿真结果表明，随着D2D用户复用数量的增加，该算法在提升系统吞吐量的同时，能有效地控制系统内部干扰，大幅度降低系统总能耗。 The simulation results show that with the increase of the number of D2D pairs, thealgorithm not only improves the system throughput, but also controls the internal interference of the systemeffectively, reduces the total energy consumption of the system greatly.
17616 容错控制平面通过将多个控制器部署在不同的网络设备上进而增强网络的可靠性，但是大量的控制器部署带来了巨大的布局成本，严重地限制了容错控制平面在实际网络中的部署与应用。 In order to deploy fault-tolerant Software-Defined Networks(SDN), many controllers must bephysically distributed among different network devices. However, a large number of controllers bring hugecosts, which limits severely the application of the fault-tolerant control plane to the real networks.
17617 为了解决上述问题，该文首先构造了容错控制平面的最小覆盖布局模型，然后设计了一种基于局部搜索策略的启发式控制器布局算法，避免搜索结果陷入局部最优解。 In order to solve the above problems, the fault-tolerant control plane is analyzed and a mathematical model that covers all switches using the least number of controllers is constructed. Then, a heuristic controller placement algorithmbased on the local search strategy is proposed to avoid the local optimal solution.
17618 在不同规模网络中的仿真结果表明，相对于其他算法，所提算法可以在保证网络容错需求的同时，降低网络中部署控制器的数量。 The experimental results show that compared with other algorithms, the proposed algorithm can effectively reduce the number of required controllers while ensuring network fault tolerance requirements in different scale networks.
17619 获取信号稀疏度对压缩感知(CS)性能的提升有重大意义，但在采样端不进行完整信号数字化采集和存储的情况下，对信号稀疏度进行估计比较困难。 Signal sparsity is of great significance for the improvement of Compressive Sensing (CS) performance.However, it is difficult to estimate the sparsity when the whole signal is not captured and stored at thesampling side.
17620 现有方法在稀疏度估计性能和计算复杂度方面难以取得较好的平衡。 Few existing mothed can achieve good balance in terms of the sparsity estimation performanceand the computational complexity.
17621 针对采样端对信号特性未知的监控视频应用，该文提出一种新的使用能量匹配的自适应速率压缩感知方法(ARCS-EM)， For the monitoring video applications where the signal characteristics isunknown for sampling devices, a new Adaptive-Rate CS using Energy Matching (ARCS-EM) method isproposed.
17622 通过观测一个恒定低速率的压缩感知观测结果来对当前帧实际稀疏度进行估计，然后根据估计结果决定当前帧应执行的压缩感知测量数，再进行补充测量得到当前帧的优化压缩感知采样结果。 By observing the measurement results of a low-rate compressive sensing, the actual sparsity of thecurrent frame is estimated and then the rate of measurement for the current frame is determined. Finally,supplementary measurements are performed to obtain the optimized compressive sensing result for the currentframe.
17623 实验结果表明，该方法可以较好地适应视频中前景稀疏度的变化，为每帧图像分配适当的压缩感知测量速率，在不显著提高采样端计算复杂度的前提下，有效提高重建视频的质量。 Experiment results show that the proposed method could allocate suitable measurement rate for eachframe to adapt to the variation of sparsity in different frames. The quality of reconstructed videos is effectivelyimproved without noticeably increasing computational complexity in the sampling side.
17624 网络空间是所有信息系统的集合，是人类赖以生存的信息环境。 Cyberspace is a collection of all information systems, which refers to the information environment forhuman survival.