相关熵与循环相关熵信号处理研究进展

邱天爽

doi:10.11999/JEIT190646

引用本文: 邱天爽. 相关熵与循环相关熵信号处理研究进展[J]. 电子与信息学报, doi: 10.11999/JEIT190646 shu

Citation: Tianshuang QIU. Development in Signal Processing Based on Correntropy and Cyclic Correntropy[J]. Journal of Electronics and Information Technology, doi: 10.11999/JEIT190646 shu

Development in Signal Processing Based on Correntropy and Cyclic Correntropy

Tianshuang QIU ^,

Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China

Corresponding author: Tianshuang QIU,qiutsh@dlut.edu.cn

Received Date: 2019-08-28
Accepted Date: 2019-11-05
Available Online: 2019-01-01
Fund Project: The National Natural Science Foundation of China (61671105, 61172108, 61139001, 81241059)

Abstract: In radio monitoring and target location applications, the received signals are often affected by complex electromagnetic environment, such as impulsive noise and cochannel interference. Traditional signal processing methods based on second-order statistics often fail to work properly. The signal processing methods based on fractional lower order statistics also encounter difficulties due to their dependence on prior knowledge of signals and noises. In recent years, the theory and method of correntropy and cyclic correntropy signal processing, which are widely concerned in the field of signal processing, are put forward. They are effective technical means to solve the problems of signal analysis and processing, parameter estimation, target location and other applications in complex electromagnetic environment. They promote greatly the development of the theory and application of non-Gaussian and non-stationary signal processing. This paper reviews systematically the basic theory and methods of correntropy and cyclic correntropy signal processing, including the background, definition, properties and characteristics of correntropy and cyclic correntropy, as well as their mathematical and physical meanings. This paper introduces also the applications of correntropy and cyclic correntropy signal processing in many fields, hoping to benefit the research and application of non-Gaussian and non-stationary statistical signal processing.

Key words:

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图 1 2D空间CIM等高线图^[5]

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图 2 循环相关熵谱与常规的循环相关谱及分数低阶循环相关谱的对比^[6]

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