ID 原文 译文
20195 实验结果证明，CPSA算法能够有效解决调度死锁问题、降低流应用执行时间并提高调度成功率。 The experimental results show this algorithmcan avoid scheduling deadlock, reduce the execution time of flow applications and improve scheduling successrate.
20196 与其它调度算法相比，对流应用执行时间的平均优化比例达到6.13%～19.53%。 The optimization ratio of total execution time of flow applications achieves 6.13%～19.53% averagely compared with other scheduling algorithms.
20197 多基外辐射源雷达定位系统受系统偏差影响较大。 The system biases degrade seriously the location precision for the multi-static passive radar system.
20198 该文针对多基外辐射源雷达到达角度(DOA)和到达时差(TDOA)联合定位系统，提出一种基于约束总体最小二乘(CTLS)的无源定位和误差校正算法。 A joint registration and passive localization algorithm based on Constrained Total Least Squares (CTLS) using Direction Of Arrival (DOA) and Time Difference Of Arrival (TDOA) measurements is developed to address the multi-static radar localization problem under the influence of system biases.
20199 首先引入辅助变量，将DOA和TDOA非线性观测方程进行线性化处理。 Firstly, the nonlinear DOA andTDOA measurement equations are linearized by introducing auxiliary variables.
20200 考虑伪线性化后定位方程中噪声矩阵各分量统计相关特性，将无源定位与误差校正联合优化问题建立为CTLS模型，并采用牛顿迭代方法对模型求解。 Considering the statistical correlation properties of the noise matrix in the pseudo-linear equations, a joint biases registration and passive localization problem is formulated as a CTLS problem and the Newton’s method is applied to solving the CTLSproblem.
20201 在此基础上，考虑辅助变量与目标位置的关联性，设计关联最小二乘算法改进目标位置估计值，采用后验迭代方法进一步提高系统偏差估计精度。 Moreover, a dependent least squares algorithm is designed to improve the target position estimation using the relationship between auxiliary variables and target position. An iterative post-estimate procedure is exploited to enhance further the estimation accuracy of the system biases.
20202 最后推导了算法的理论误差。 Finally, the theoretical error of the proposed algorithm is derived.
20203 仿真结果表明：该算法能够有效地估计目标位置和系统偏差。 Simulations demonstrate that the proposed algorithm can effectively estimate the system biases and target position.
20204 针对传统指纹定位算法建库耗时长和定位精度低的问题，该文提出一种基于自适应渐消记忆的蓝牙序列匹配定位算法。 The traditional fingerprinting localization algorithm has high construct time overhead and low positioning accuracy. Because of this problem, an adaptive fading memory based bluetooth sequence matching localization algorithm is proposed.