基于CEEMDAN改进型信源个数估计算法  

Improved Source Number Enumeration Algorithm based on CEEMDAN

作　　者：钟家兴 胡耀敏 何小平 ZHONG Jia-xing;HU Yao-min;HE Xiao-ping(College of Information Engineering,Guangdong University of Technology,Guangzhou 51006,China)

机构地区：[1]广东工业大学信息工程学院,广东广州510006

出　　处：《电脑知识与技术》2021年第16期1-2,7,共3页Computer Knowledge and Technology

摘　　要：针对经验模态分解过程中存在模态混叠问题,利用自适应白噪声的完整集成经验模态分解(CEEMDAN)代替EMD对希尔伯特-黄变换加以改进,构建了一种基于CEEMDAN改进型信源估计模型。射频实验室实验结果表明,改进后的算法模型在小块拍下具有良好的估计性能。Aiming at the problem of modal aliasing in the process of empirical mode decomposition,a fully integrated empirical mode decomposition(CEEMDAN)of adaptive white noise(CEEMDAN)is used instead of EMD to improve the Hilbert-Huang transform,and an improved version based on CEEMDAN is constructed.Source estimation model.The experimental results of the radio frequency laboratory show that the improved algorithm model has good estimation performance in small shots.

关 键 词：经验模态分解 信源数估计 模态混叠 自适应白噪声的完整集成经验模态分解 小块拍 射频实验室 

分 类 号：TN911.23[电子电信—通信与信息系统]