ID 原文 译文
2143 最后利用变步长梯度上升方法，在有限次的迭代下，完成在连续概率空间中代价函数极大值求解，最终完成 RSC 码参数识别。 Finally, the varia-ble step gradient method was used to solve the maximum value of the cost function in the continuous probability space at thefinite iteration.
2144 提出的算法收敛速度快且稳定，除了具有较强的低信噪比适应能力外，其计算量与编码器寄存器个数以及码元路数成平方倍数增长。 The proposed algorithm has a fast and stable convergence speed. In addition to the strong adaptive ability oflow SNR, the computational complexity increases squarely with the number of encoder registers and the number of symbols.
2145 仿真实验表明:提出的算法最多在第 5 次迭代时，就能完成参数的收敛，同时低信噪比的适应能力较强，即使在 0dB 条件下，RSC 码多项式参数识别率能达到 90% 以上; The simulation experiment showed that the proposed algorithm could achieve the convergence of the parameters at most fifth iterations, while have strong ability to suit to the low SNR. Even the SNR is 0dB, the correct identification rate of RSC codecan reach more than 90% .
2146 与现有的相关算法相比，所提算法的低信噪比适应能力提高了近 3dB，同时完成一次参数识别的时间大大降低。 Compared with the existing algorithm, the proposed algorithm improved the adaptive capacity oflow SNR by nearly 3dB, at the same time, the time consuming is greatly reduced.
2147 针对传感器资源有限的情况，以目标检测为背景，提出了一种基于风险理论的传感器管理方法。 A sensor management method with the limited sensor resources under target detecting is proposed based onrisk theory.
2148 首先建立目标检测模型和传感器辐射模型，将“检测风险”和“截获风险”之和作为传感器管理风险函数，即目标函数。 Firstly, the target detection model and the sensor radiation model are established, with‘detecting risk'and‘ra-diating risk'defined. The sum of the two kinds of risk is taken as the sensor management risk function, namely the objective function.
2149 其次为对模型求解，将预测值的期望值作为目标函数的近似值，重新修正目标函数。 Secondly, to get a scheme from the function, the predicted expectation value is taken as the approximation of theobjective function, then the objective function is revised.
2150 接着设计了基于多 Agent 的分布式优化算法。 After that, a distributed optimization algorithm based on multi-agentis proposed.
2151 仿真实验表明，通过本文提出的基于风险理论的传感器管理方法，能够有效实现传感器管理， The experiment results show that the proposed sensor management method based on risk theory can effectivelyresolve the problem of sensor management.
2152 与以往的传感器管理方法相比，本文方法更能较好地解决资源有限情况下的传感器管理问题。 This method outperforms the previous sensor management method and could solve the problem of sensor management under limited resources with a better solution.