个人信息Personal Information
教授
博士生导师
硕士生导师
主要任职:Professor at the Institute of Advanced Measurement & Control Technology
其他任职:先进检测与控制技术研究所所长
性别:男
毕业院校:上海交通大学
学位:博士
所在单位:控制科学与工程学院
学科:控制理论与控制工程. 化学工程
办公地点:大连理工大学控制科学与工程学院先进检测与控制技术研究所
大连市凌工路2号大连理工大学海山楼A座724室
联系方式:Tel:(0411)84706465 实验室网站:http://act.dlut.edu.cn/
电子邮箱:tliu@dlut.edu.cn
Hyperbolic-tangent-function-based cyclic correlation: Definition and theory
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论文类型:期刊论文
发表时间:2019-11-01
发表刊物:SIGNAL PROCESSING
收录刊物:SCIE、EI
卷号:164
页面范围:206-216
ISSN号:0165-1684
关键字:Cyclostationary; Non-Gaussian noise; Impulsive noise; Hyperbolic tangent function
摘要:Non-stationary, non-Gaussian signal processing is a challenging topic in signal processing research. Over the past decade, due to effectively addressing co-channel interference, cyclostationarity-based methodologies have found a wide range of applications, such as wireless communication, cognitive radio, and mechanical vibration monitoring. Despite offering a feasible scheme, the second and higher-order cyclostationarity-based methodologies suffer under non-Gaussian noise environments, particularly impulsive noise environments. In this paper, through studying the similarity measurement, nonlinear function, and mapping mode, we propose a novel methodology named hyperbolic-tangent-function-based cyclic correlation (HTCC) to address both Gaussian and non-Gaussian noises with a uniform expression. The idea is inspired by the fact that hyperbolic tangent function is not only a bounded function but also achieves a differential compression. In addition, the theoretical foundations of this novel method are introduced step by step, including the definition, property, and spectrum. A number of numerical experiments are carried out to compare the algorithm performance with existing competitive methods. The proposed method generally shows good effectiveness and robustness and can be utilized for denoising problems in signal processing. (C) 2019 Elsevier B.V. All rights reserved.