| ID | 原文 | 译文 |
| 51237 | 通过自适应改变延时阀值因子实现多业务的差异化调度， | through the adaptive change of time-delay valve value factor to realize the business differentiation scheduling, |
| 51238 | 从而优化AOS虚拟信道服务质量及调度性能。 | thus optimizing the AOS service quality and virtual channel scheduling performance. |
| 51239 | 采用多信源重尾分布的ON/OFF流量分布模型进行仿真验证，实验结果表明，针对自相似业务流，SDAAP算法在溢出率、平均延迟等方面优于AOS固定阀值和等时调度算法。 | Multi source of heavy-tailed ON/OFF traffic distribution model simulation, the experimental results show that for the self-similar traffic stream SDAAP algorithm in such aspects as overflow ratio, average delay is superior to the AOS fixed threshold and scheduling algorithm etc. |
| 51240 | 针对现有扩展卡尔曼滤波算法在协同定位应用计算复杂的问题，提出一种基于联合分布状态的信息滤波算法，并将其运用在多机器人协同定位中。 | In view of the existing extended kalman filtering algorithm in application co-location computing complex problems, put forward a kind of information filtering algorithm based on joint distribution state, and its use in multi-robot cooperative localization. |
| 51241 | 从3个方面解决计算复杂的问题: | Solve the problem of calculating complex from three aspects: |
| 51242 | 第一，借鉴机器人同步构图与定位，利用联合分布状态将关键历史状态保留在滤波中，避免时间更新的复杂计算; | first, draw lessons from robot synchronization composition and positioning, using the joint distribution status, keep the key historical status in filtering, avoid complex calculation time update; |
| 51243 | 第二，利用滤波信息参数的稀疏性，减小滤波所涉及的计算复杂度; | Second, make use of information filtering parameter is sparse, decreasing filtering computing complexity involved; |
| 51244 | 第三，根据Cholesky矩阵分解的特殊性质， | Third, based on the special properties of the matrix Cholesky decomposition, |
| 51245 | 进一步减少计算复杂度， | further reduce the computational complexity, |
| 51246 | 节省存储空间， | saving storage space, |