ID 原文 译文
21155 首先，使用多普勒频移计算节点间相对移动速度，预测节点移动性，得到节点间链路保持时间。 First, the Doppler shift is used to calculate the relative moving speed and obtain the linkexpiration time between nodes.
21156 然后，在簇形成阶段，采用面向节点稳定性的MAX-MIN启发式算法，根据节点的平均链路保持时间对簇首进行选择。 Then, during the cluster formation stage, the MAX-MIN heuristic algorithm isused to select the cluster head according to the average link expiration time of the node.
21157 进而，在簇保持阶段，提出一种基于节点运动状态的网络自适应调整算法， Furthermore, during the cluster maintenance stage, a network adaptive adjustment method is proposed based on node motion.
21158 一方面调整节点信息数据发送周期以平衡数据开销和精确度， On the one hand, the node information transmission cycle is adjusted to balance the data overhead and accuracy;
21159 另一方面通过预测节点间链路通断情况调整分簇结构，以减少链路失效时的链路重建时间，提高网络运行质量。 On the other hand, the cluster structure is adjusted by predicting the link disconnection to reduce link reconstruction time and improve the quality of network operation.
21160 仿真实验表明，所提算法可以有效延长簇首持续时间，提高簇结构在动态环境下的稳定性。 Simulation results show that the proposed algorithm can effectively prolong the duration of cluster head and improve the stability of cluster structure in dynamic environment.
21161 针对系统误差导致光流计算稳健性较差及精度较低的问题，该文提出一种基于小波多分辨理论的稳健光流计算方法。 Focusing on the issue that the systematic errors lead to poor robustness and low accuracy of optical flow calculation, a robust optical flow calculation method is proposed in this paper, which is based on the wavelet multi-resolution theory.
21162 所提算法基于小波多尺度分辨率特性，将光照条件变化及传感器噪声引起的系统误差包含进光流计算中以改善光流计算的稳健性及估计精度，并通过总体最小二乘法求解超定小波光流方程组以获得光流矢量。 With the multi-resolution characteristics of wavelet, the system error causedby variation of illumination conditions and sensor noise is incorporated into the calculation of optical flow toimprove the robustness and estimation accuracy. In what follows, the total least square method is used to solvethe over-determined wavelet optical flow equations to obtain the optical flow vector.
21163 仿真结果表明，与传统的Lucas-Kanade算法、Horn-Schunck算法及基于小波的全向图像光流估计方法相比，所提算法可显著改善光流估计精度及稳健性。 As compared to thetraditional Lucas-Kanade approach, Horn-Schunck method and optical flow estimation in omnidirectionalimages using wavelet approach, simulation results show that the proposed algorithm can significantly improvethe accuracy of optical flow estimation and the robustness of the optical flow field.
21164 Wi-Fi室内定位技术是目前移动计算领域的研究热点之一，而传统位置指纹定位方法没有考虑复杂室内环境下Wi-Fi信号分布的多样性问题，从而导致Wi-Fi室内定位系统的鲁棒性较差。 Wi-Fi indoor localization technique is one of the current research hotspots in the field of mobile computing, however, the conventional location fingerprinting based localization scheme does not consider the diversity of Wi-Fi signal distribution in the complicated indoor environment, resulting in the low robustness of indoor localization system.