ID 原文 译文
39116 数值仿真表明，所提方法可获得的DME干扰功率衰减值约41 dB，有效克服了DME脉冲干扰对L-DACS1系统接收机的影响。 Numerical simulation shows that using the proposed method in this paper, DME interference power can be attenuated about 41 dB, which effectively overcomes the impact of DME pulse interference on the receiver of L-DACS1 system.
39117 针对实际监控场景中经常遇到的人脸图像分辨率较低的问题，本文提出了一种利用松弛耦合非负矩阵分解的低分辨率人脸识别算法(RCNMF)。 In order to solve the problem of low resolution of face image in the actual monitoring scene, this paper proposes a algorithm for low resolution face image recognition which utlize the relaxation coupled nonnegative matrix factorization(RCNMF).
39118 首先，对高低分辨率人脸图像进行非负矩阵分解(NMF)，同时使高低分辨率人脸图像的组合系数保持松弛耦合，从而得到含有原图像特征信息的基矩阵。 Firstly, the nonnegative matrix factorization(NMF) is performed for both high-resolution and low-resolution face images. Meanwhile, the combination coefficients of high-resolution and low-resolution face images are kept loose coupling, so as to obtain the basis matrices with feature information of original face images.
39119 然后，通过低分辨率图像的基矩阵提取训练和测试样本的特征。 Secondly, the features of training samples and test samples are extracted by the basis matrix of low resolution images.
39120 最后进行识别。 Finally, the identification process is carried out.
39121 实验结果验证了与其他几种基于耦合映射的低分辨率人脸识别方法相比，RCNMF算法的识别性能更好。 Our experiments verify that the proposed RCNMF algorithm is more effective to solve low resolution face recognition problem than the other state-of-the-art methods based on coupled mapping.
39122 同时通过实验验证了RCNMF算法的收敛性。 At the same time, the convergence of the proposed RCNMF algorithm is verified by experiments.
39123 在免调度非正交多址接入(Non-Orthogonal Multiple Access，NOMA)系统中，针对基于帧的多用户传输场景的信道估计(Channel Estimation，CE)与用户的活跃和数据检测(Multiuser Detection，MUD)问题，本文在多重测量矢量压缩感知(Multiple Measurement Vector-Compressive Sensing，MMV-CS)框架下，提出了一种门限辅助的分布式弱选择分段自适应匹配追踪(Thresholod Aided-Distributed Weak Selection Stagewise Adaptive Matching Pursuit，TA-DWSStAMP)算法来联合解决CE和MUD问题。 For the channel estimation(CE) and the multiuser detection(MUD) with active user detection and data detection problems in the grant-free non-orthogonal multiple access(NOMA) system, this paper proposes a threshold aided-distributed weak selection stagewise adaptive matching pursuit(TA-DWSStAMP) algorithm to jointly solve the CE and MUD problems in the multiple measurement vector-compressive sensing(MMV-CS) model.
39124 该算法在精确的迭代终止准则下，引入阶段标识，在大步长阶段设计了一种幂函数型的变步长方法。 The algorithm terminates at precise iterations under the criterion and introduces a new identification parameter. When the identification parameter represents a large step, a variable step size method based on power function is designed.
39125 仿真结果表明，本文提出的算法能够在复杂度仅为现有算法10%的条件下，获得与现有算法相近的信道估计性能、用户成功活跃检测率和用户数据的误符号率。 Simulation results show that, as compared to the existing algorithm, the proposed TA-DWSStAMP algorithm can obtain similar successful activity detection rate of the users, symbol error rate of the user data and the normalized mean squared error performance of the channel estimation. However, its computational complexity only accounts for about 10% of the existing algorithm.