| ID | 原文 | 译文 |
| 4213 | 最后利用长短时记忆加全卷积网络提取无意调相序列的联合特征，实现雷达辐射源个体自动识别。 | Finally, the LSTM-FCN wasused to extract the joint features of UPMOP sequence to realize the radar specific emitter automatic identification. |
| 4214 | 仿真实验以及实测数据实验均验证了所提算法的可行性与有效性，实验结果表明，所提算法识别正确率高、耗时短。 | Both the simulation experiments and the measured data experiments verify the feasibility and effectiveness of the proposed al-gorithm. Moreover, the proposed algorithm has high identification accuracy and short time consumption. |
| 4215 | 针对终端电量耗尽的问题，提出将终端电池状态信息考虑到 SWIPT 传输策略中，并提供了一种速率公平传输策略。 | To solve the battery depletion problem, the terminals' battery status information (BSI) was proposed to be tak-en into consideration in simultaneous wireless information and power transfer (SWIPT) strategies, and a SWIPT strategyto guarantee the rate fairness was provided. |
| 4216 | 所提方案利用终端电池状态信息限制终端可容忍的最大速率及能量，以最大化最小用户速率为优化目标，以速率/能量需求以及终端可容忍的最大速率/能量为限制条件，优化发送功率与功率分流因子。 | BSI determined the terminals' sufferable received rate and harvested energy.The proposed scheme was formulated as an optimization problem to max-min user rate, with rate/energy requirementconstraints and the sufferable rate/energy constraints. |
| 4217 | 为了求解该优化问题，首先根据电池电量对终端进行分类，然后利用提出的基于交替优化的算法进行求解。所提方案通过合理分配发送功率与功率分流因子，控制较低电量用户的接收速率，以避免其所需能量消耗超过电池电量。 | To solve optimization problem, the receivers were firstly classifiedwith their battery level, then the optimal solutions were obtained by the proposed iteration optimization-based algorithm.With the proposed scheme, the transmit power and the power splitting factor would be controlled and the data rate at re-ceivers, especially the receivers that with lower battery level would be restricted, avoiding the required battery consump-tion to exceed battery level. |
| 4218 | 仿真结果表明，所提方案延长了用户电池寿命且避免了电池电量的耗尽，其用户速率公平性随着用户间电池电量差距的减小而提升。 | Simulation results reveal that the proposed scheme can prolong battery lifetime and avoid thebattery depletion problem, and its fairness performance is strengthened with the difference decreasing among the receiv-ers' battery level. |
| 4219 | 针对传统的直觉模糊 c 均值聚类算法进行图像分割时对聚类中心敏感导致最终聚类精度低、细节保留性差、时间复杂度较大等不足，提出了一种适用于电力设备红外图像分割的基于分布信息的直觉模糊 c 均值聚类算法。 | Due to the sensitivity of the traditional intuitionistic fuzzy c-means (IFCM) clustering algorithm to theclustering center in image segmentation, which resulted in the low clustering precision, poor retention of details,and large time complexity, an intuitionistic fuzzy c-means clustering algorithm was proposed based on spatial dis-tribution information suitable for infrared image segmentation of power equipment. |
| 4220 | 红外图像中高强度的非目标对象与图像强度不均匀对图像分割有较强干扰，所提算法能有效抑制该干扰。 | The non-target objects with high intensity and the non-uniformity of image intensity in the infrared image had strong interference to the imagesegmentation, which could be effectively suppressed by the proposed algorithm. |
| 4221 | 首先，将高斯模型引入电力设备的全局空间分布信息中以改进 IFCM 算法； | Firstly, the Gaussian model wasintroduced into the global spatial distribution information of power equipment to improve the IFCM algorithm. |
| 4222 | 其次，利用局部空间信息的空间算子优化隶属函数来解决边缘模糊和图像强度不均匀问题。 | Secondly, the membership function was optimized by local spatial operator to solve the problem of edge blur andimage intensity inhomogeneity. |