Study on High Efficient Algorithm for Cyclic Correntropy Spectral Analysis

Hui LI

doi:10.11999/JEIT200113

Volume 43 Issue 2

Feb. 2021

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Hui LI. Study on High Efficient Algorithm for Cyclic Correntropy Spectral Analysis[J]. Journal of Electronics & Information Technology, 2021, 43(2): 310-318. doi: 10.11999/JEIT200113

Citation:

Hui LI. Study on High Efficient Algorithm for Cyclic Correntropy Spectral Analysis[J]. Journal of Electronics & Information Technology, 2021, 43(2): 310-318. doi: 10.11999/JEIT200113

Hui LI. Study on High Efficient Algorithm for Cyclic Correntropy Spectral Analysis[J]. Journal of Electronics & Information Technology, 2021, 43(2): 310-318. doi: 10.11999/JEIT200113

Citation:

Hui LI. Study on High Efficient Algorithm for Cyclic Correntropy Spectral Analysis[J]. Journal of Electronics & Information Technology, 2021, 43(2): 310-318. doi: 10.11999/JEIT200113

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Study on High Efficient Algorithm for Cyclic Correntropy Spectral Analysis

doi: 10.11999/JEIT200113

Hui LI^,

School of Mechanical Engineering, Tianjin University of Technology and Education, Tianjin 300222, China

Funds: The National Natural Science Foundation of China (51375319)

Received Date: 2020-02-21
Rev Recd Date: 2021-01-08

Available Online: 2021-01-12

Publish Date: 2021-02-23

Abstract

Abstract

A high computationally efficient algorithm for cyclic correntropy spectral analysis is presented which is named as Correntrogram algorithm. Correntrogram algorithm overcomes the problems of Cyclic Periodogram Detection (CPD) method, such as high computational cost, low resolution and spectrum leakage. Correntrogram utilizes the advantages of Wigner-Ville Distribution (WVD) which has high time frequency resolution. By replacing the time-varying autocorrelation function with the time-varying auto-correntropy function in the WVD algorithm, the cyclic auto-correntropy spectral density estimation algorithm can be realized. First, the time-varying auto-correntropy function matrix of the signal is calculated, and then the Fast Fourier Transform (FFT) of each row of the time-varying auto-correntropy function matrix is computed to get the cyclic auto-correntropy function matrix. Finally, the FFT of each column of the cyclic auto-correntropy function matrix is calculated to get the cyclic auto-correntropy spectral density function. The validity of the proposed estimator is demonstrated on a simulative amplitude modulation signal. The simulative result shows that not only the proposed estimator is computationally efficient, but also has high frequency resolution and overcomes the spectrum leakage. The performance of Correntrogram is better than that of CPD method.
- Correntropy,
- Cyclic correntropy function,
- Cyclic correntropy spectral density function,
- Cyclostationary signals,
- Cyclic spectral analysis,
- Spectral correlation density

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References(29)

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