Quasi-Periodic Gaussian Process Modeling of Pseudo-Periodic Signals-Reference-Cited by-同舟云学术

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Quasi-Periodic Gaussian Process Modeling of Pseudo-Periodic Signals

Published:2023 Issue: Volume:71 Page:3548-3561
ISSN:1053-587X
Container-title:IEEE Transactions on Signal Processing
language:
Short-container-title:IEEE Trans. Signal Process.

Author:

Li Yongxiang¹^ORCID,Zhang Yunji¹^ORCID,Xiao Qian²^ORCID,Wu Jianguo³^ORCID

Affiliation:

1. Department of Industrial Engineering and Management, Shanghai Jiao Tong University, Shanghai, China

2. Department of Statistics, University of Georgia, Athens, GA, USA

3. Department of Industrial Engineering and Management, Peking University, Beijing, China

Funder

National Natural Science Foundation of China

Shanghai Pujiang Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/78/10040758/10256149.pdf?arnumber=10256149

Reference64 articles.

1. Maximum Likelihood Line Spectral Estimation in the Signal Domain: A Rank-Constrained Structured Matrix Recovery Approach

2. On Local Chirp Rate Estimation in Noisy Multicomponent Signals: With an Application to Mode Reconstruction

3. A Noise Resistant Correlation Method for Period Detection of Noisy Signals

4. Extended Noise Resistant Correlation Method for Period Estimation of Pseudoperiodic Signals

5. Modelling quasi-periodic signals in geodetic time-series using Gaussian processes

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1. Regularized Periodic Gaussian Process for Nonparametric Sparse Feature Extraction From Noisy Periodic Signals;IEEE Transactions on Automation Science and Engineering;2024

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