ID 原文 译文
47296 实现智能地选择信号分量、过滤噪声分量，提高测量数据信噪比； The optimizedmeasurement matrix can selectively sense the sparse signal and suppress the noise to improve the SNR of themeasurement data, resulting in the improvement of sparse reconstruction performance.
47297 最后，通过增加测量数据获取次数可进一步提升算法重构性能。 Finally, it was pointed out thatincreasing the measurement times can further enhance the performance of denoising reconstruction.
47298 仿真实验表明，基于选择性测量的压缩感知去噪重构算法明显改善了低信噪比条件下信号的重构性能。 Simulation resultsshow that the proposed denoising reconstruction algorithm has a better improvement in the performance of reconstruction ofnoisy signal, especially under low SNR.
47299 针对当前关于服务路径构建问题的研究主要围绕单一优化目标，构建时延最小、开销最低或负载均衡的服务路径，忽略了服务路径的综合质量，提出了一种基于离散粒子群优化的多目标服务路径构建算法(MOPSO)。 Aiming at previous research primarily focused on constructing service paths with a single objective, forexample, latency minimization, cost minimization or load balance, which ignored the overall performance of constructedservice paths, a multi-objective service path constructing algorithm based on discrete particle swarm optimization(MOPSO) was proposed.
47300 为了提高收敛速度，优化算法的性能，进一步研究了候选节点和路径的评价标准，提出一种粒子位置初始化和更新策略(PIFC)。 To promote the convergence rate and improve constructing performance, the criterions forselecting candidate physical nodes and paths were explored, and a particle position initialization and update strategy(PIFC) was designed.
47301 仿真实验表明，与已有算法相比，所提出的算法有效地优化了服务路径的质量，提高了服务路径的构建成功率和长期平均收益。 Simulation experiments show that the proposed algorithms can improve the overall quality ofservice paths and increase the success rate and long-term average revenue.
47302 研究了频率非选择性瑞利衰落信道中的物理层网络编码系统容量问题。 The capacity issue of a denoise-and-forward(DNF) protocol was focused on based PNC system of frequencynon-selective Rayleigh fading channel.
47303 理论推导了基于解噪重传协议的系统容量， First, the total sum-rate of the system was derived.
47304 根据容量解析式给出了系统和容量最大化的 2 个条件表达式， With the derived sum-rate expression,two policies maximizing the system sum-rate are proposed.
47305 提出了一种最大化系统和容量的自适应分集策略。 On this basis, a novel adaptive diversity scheme was proposed.