ID 原文 译文
17975 为实现全盲条件下的调制识别，在进行ICA分离前，利用最小描述长度(MDL)准则估计发射天线数。 In order to realize modulation recognition under completely blind condition, theMinimum Description Length (MDL) criterion is used to estimate the number of transmitting antennas before ICA separation.
17976 在得到发射信号之后，首先利用6阶累积量、循环谱和4次方谱算法构造4个特征参数，然后利用分层结构的神经网络分类器识别信号的调制类型。 After obtaining the transmitted signal, four characteristic parameters are constructed by usingsix-order cumulant, cyclic spectrum and fourth-power spectrum algorithm, and then the modulation type of thesignal is identified by using hierarchical neural network classifier.
17977 仿真结果表明，所提方法可在较低信噪比下对{2PSK, 2ASK,2FSK, 4PSK, 4ASK, MSK, 8PSK, 16QAM}8种MIMO信号进行有效识别，当发送天线数为2、接收天线数为5、信噪比为2 dB时，识别率可达到98%以上。 The simulation results show that the proposedmethod can effectively recognize {2PSK, 2ASK, 2FSK, 4PSK, 4ASK, MSK, 8PSK, 16QAM} eight MIMOsignals at low SNR. When the number of transmitting antennas is 2, the number of receiving antennas is 5 andthe SNR is 2dB, the recognition rate can reach more than 98%.
17978 针对非高斯背景干扰下的弱信号检测需求，在综述高斯化处理与扩展匹配滤波概念及思路的基础上，该文提出了两种基于对称α稳定分布建模的高斯化处理方法，构建了相应的扩展匹配滤波检测器，并对比早先建立的混合高斯分布下的高斯化处理，对其高斯化效果、对应检测性能、运行速度等进行了仿真研究。 Considering the requirement for weak signal detection in non-Gaussian background interference, afterconceptions and ideas summarizing for Gaussianization processing and extended matched filter, twoGaussianizaiton filters and corresponding detections are proposed based on symmetric alpha-stable distributionmodeling, comparing with those under Gaussian mixture modeling proposed earlier. All these Gaussianizationfilters and extended matched filters are realized in simulation. Their performances, such as Gaussianzing effect,detecting capability and running time are studies in system.
17979 研究表明，高斯化处理可以降低背景干扰的非高斯性，从而提高后续匹配滤波的检测性能； Some conclusions are reached: Gaussianization can improve the detecting performance of the succeeding matched filter because of its restraining of big impulsive samples;
17980 基于对称α稳定分布的高斯化处理，在保持性能的同时，具有更高的运行效率。 Gaussianization filters under symmetric alpha-stable distribution modeling have higher operatiing efficiency while their peformance are similar to those under Gaussian mixture modeling.
17981 受光场相机微透镜几何标定精度的影响，4D光场在角度方向上的解码误差会造成积分后的重聚焦图像边缘信息损失，从而降低全聚焦图像融合的精度。 Affected by the micro-lens geometric calibration accuracy of the light field camera, the decoding errorof the 4D light field in the angular direction will cause the edge information loss of the integrated refocusedimage, which will reduce the accuracy of the all-in-focus image fusion.
17982 该文提出一种基于边缘增强引导滤波的光场全聚焦图像融合算法，通过对光场数字重聚焦得到的多幅重聚焦图像进行多尺度分解、特征层决策图引导滤波优化来获得最终全聚焦图像。 In this paper, a light field all-in-focusimage fusion algorithm based on edge-enhanced guided filtering is proposed. Through multi-scale decompositionof the digital refocused images and guided filtering optimization of the feature layer decision map, the final all-in-focus image is obtained.
17983 与传统融合算法相比，该方法对4D光场标定误差带来的边缘信息损失进行了补偿，在重聚焦图像多尺度分解过程中增加了边缘层的提取来实现图像高频信息增强，并建立多尺度图像评价模型实现边缘层引导滤波参数优化，可获得更高质量的光场全聚焦图像。 Compared with the traditional fusion algorithm, the edge information loss caused bythe 4D light field calibration error is compensated in the presented method. In the step of multi-scaledecomposition of the refocused image, the edge layer extraction is added to accomplish the high-frequencyinformation enhancement. Then the multi-scale evaluation model is established to optimize the edge layer’sguided filtering parameters to obtain a better light field all-in-focus image.
17984 实验结果表明，在不明显降低融合图像与原始图像相似性的前提下，该方法可有效提高全聚焦图像的边缘强度和感知清晰度。 The experimental results show that the edge intensity and the perceptual sharpness of the all-in-focus image can be improved without significantly reducing the similarity between the all-in-focus image and the original image.