ID 原文 译文
24175 并提出一个基于 Benders 分解的联合优化策略，控制基站活跃/休眠状态，实现网络容量与吞吐量间的平衡。 Then a Benders decomposition based joint optimization strategy is proposed to balance capacity with throughout via controlling on-off state of BS.
24176 仿真结果表明，该机制可在不增加发射功率的条件下实现覆盖补偿，并在至多42.6%的基站休眠时，仍能满足网络的基本性能要求。 The simulation results show that up to 42.6% of BS can be dormant while meeting basic network performance requirements. Furthermore, the coverage can be compensated without increasing transmitting power in the proposed mechanism.
24177 基于稀疏表示的分类方法由于其所具有的简单性和有效性获得了研究者的广泛关注，然而如何建立字典原子与类别信息间的联系仍然是一个重要的问题，与此同时大部分稀疏表示分类方法都需要求解受范数约束的优化问题，使得分类任务的计算较复杂。 Classification method based on sparse representation has won wide attention because of its simplicity and effectiveness, while how to adaptively build the relationship between dictionary atoms and class labels is still an important open question, at the same time most of the sparse representation classification methods need to solve a norm constraint optimization problem, which increases the computational complexity in the classification task.
24178 为解决上述问题，该文提出一种新的基于 Fisher 约束的字典对学习方法。新方法联合学习结构化综合字典和结构化解析字典，然后通过样本在解析字典上的映射直接求解稀疏系数矩阵； To address this issue, this paper proposes a novel Fisher constraint dictionary pair learning method to jointly learn a structured synthesis dictionary and a structured analysis dictionary, then directly obtains the sparse coefficient matrix by analysis dictionary.
24179 同时采用 Fisher 判别准则编码系数使系数具有一定的判别性。 In this paper, the Fisher criterion is used to encode the coefficients.
24180 最后将新方法应用到图像分类中，实验结果表明新方法在提高分类准确率的同时还大大降低了计算复杂度，相较于现有方法具有更好的性能。 Finally the new method is applied to image classification task, the experimental results show that the new method not only improves the accuracy of classification but also greatly reduces the computational complexity. Compared with the existing methods, the new method has better performance.
24181 分布式微小卫星 SAR 是实现小型化、低成本星载 SAR 系统的重要途径，然而，在该体制下，如何充分利用分布式系统资源，实现高分辨率成像是其面临的关键问题之一。 Distributed micro-satellites SAR has the capabilities of substantially miniaturizing the size and lowering the cost of space-borne SAR systems. However, one of the key issues is to take full advantage of the distributed resources and achieve high-resolution images.
24182 该文提出一种利用 LFMCW 信号实现分布式微小卫星平台 SAR 的方法，并基于方位向编队飞行的微小卫星构型，对其信号模型与高分辨率成像方法进行了研究。 In this paper, an approach utilizing LFMCW signal is proposed to realize distributed micro-satellites SAR system. The signal model and the high-resolution imaging method is studied on the basis of the serial formation in azimuth.
24183 该文方法使用多颗微小卫星同时发射与接收频分 LFMCW 信号，利用交叉接收的构型使不同频带收发天线所形成的等效相位中心重合，进而在距离向对信号进行频带合成以恢复全带宽信号，从而实现高分辨率 SAR 成像。 LFMCW signals are transmitted simultaneously and beat-frequency division signals are received by different micro-satellites. With the use of the crossed receiving technique, different sub-band signals with superposed equivalent phase centers can be acquired by the configuration design of formation flying, and then the full-bandwidth signal is synthesized to obtain high-resolution image.
24184 该方法实现了分布式平台信号的频带合成，为高分辨率 LFMCW SAR 技术在微小卫星平台上的应用提供了理论支撑。 The proposed method synthesizes the sub-band signals of distributed platforms, which provides theoretical support for applying high-resolution LFMCW signals in the field of distributed micro-satellites SAR.