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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Three-dimension extracting transform
Xiangxiang Zhu, Zhuosheng Zhang, Jinghuai Gao
Signal Processing (2020) Vol. 179, pp. 107830-107830
Closed Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

High-Dimensional Synchrosqueezing Chirplet Transform for Analyzing Signals With Multiple Nonproportional Frequencies
Dezun Zhao, Honghao Wang, Lingli Cui
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-9
Closed Access | Times Cited: 5
Local maximum synchrosqueezes from entropy matching chirplet transform
Ya He, Minghui Hu, Zhinong Jiang, et al.
Mechanical Systems and Signal Processing (2022) Vol. 181, pp. 109476-109476
Closed Access | Times Cited: 23
Self-Correcting Linear Chirplet Transform for the Separation of Signals with Crossover Frequencies
Wanyang Zhang, Taihuan Wu, Zhigang Jia, et al.
(2025)
Closed Access
Newton time-extracting wavelet transform: An effective tool for characterizing frequency-varying signals with weakly-separated components and theoretical analysis
Wenting Li, François Auger, Zhuosheng Zhang, et al.
Signal Processing (2023) Vol. 209, pp. 109017-109017
Open Access | Times Cited: 9
A sparse time-frequency reconstruction approach from the synchroextracting domain
Xuping Chen, Hui Chen, Ying Hu, et al.
Signal Processing (2024) Vol. 222, pp. 109517-109517
Closed Access | Times Cited: 3
Local maximum frequency-chirp-rate synchrosqueezed chirplet transform
Ran Zhang, Zimeng Wang, Yu Tan, et al.
Digital Signal Processing (2022) Vol. 130, pp. 103710-103710
Closed Access | Times Cited: 15
Enhanced adaptive linear chirplet transform for crossing frequency trajectories
Cristian López, Keegan J. Moore
Journal of Sound and Vibration (2024) Vol. 578, pp. 118358-118358
Closed Access | Times Cited: 2
Multiple enhanced synchrosqueezing in the time-frequency-chirprate space
Tao Chen, Lei Xie, Mingzhe Cui, et al.
Signal Processing (2024) Vol. 222, pp. 109541-109541
Closed Access | Times Cited: 2
Enhanced Time-Frequency Representation and Mode Decomposition
Haijian Zhang, Guang Hua, Yong Xiang
IEEE Transactions on Signal Processing (2021) Vol. 69, pp. 4296-4311
Open Access | Times Cited: 16
Two dimensional local maximum synchroextracting chirplet transfrom and application of characterizing micro-Doppler signals
Ran Zhang, Xingxing Liu, Yu Tan, et al.
Signal Processing (2022) Vol. 198, pp. 108598-108598
Closed Access | Times Cited: 12
A statistical frequency-chirprate extractor for mode retrieval with crossover instantaneous frequencies
Hui Chen, Xinyu Zhou, Xuping Chen, et al.
Signal Processing (2023) Vol. 212, pp. 109174-109174
Closed Access | Times Cited: 5
High-dimensional extracting chirplet transform for fault diagnosis of wind turbines
Dezun Zhao, Honghao Wang, Tianyang Wang, et al.
IEEE Sensors Journal (2024) Vol. 24, Iss. 16, pp. 25404-25413
Closed Access | Times Cited: 1
Spatial-Domain Synchrosqueezing Wavelet Transform and Its Application to Seismic Ground Roll Suppression
Haoran Lin, Lei Xing, Qianqian Li, et al.
IEEE Transactions on Geoscience and Remote Sensing (2022) Vol. 60, pp. 1-16
Closed Access | Times Cited: 7
Time-Extracting Wavelet Transform for Characterizing Impulsive-Like Signals and Theoretical Analysis
Wenting Li, Zhuosheng Zhang, François Auger, et al.
Circuits Systems and Signal Processing (2023) Vol. 42, Iss. 7, pp. 3873-3901
Closed Access | Times Cited: 3
Scatterer-Level Time-Frequency-Frequency Rate Representation for Micro-Motion Identification
Honglei Zhang, Wenpeng Zhang, Yongxiang Liu, et al.
Remote Sensing (2023) Vol. 15, Iss. 20, pp. 4917-4917
Open Access | Times Cited: 3
Automatic instantaneous frequency estimator for multicomponent signals with the variable number of components
Yongchun Miao
Signal Processing (2022) Vol. 197, pp. 108541-108541
Closed Access | Times Cited: 5
Self-matched extracting wavelet transform and signal reconstruction
Wenting Li, François Auger, Zhuosheng Zhang, et al.
Digital Signal Processing (2022) Vol. 128, pp. 103602-103602
Closed Access | Times Cited: 5
Skeleton-based reassignment of nonstationary signals spectrogram
Vittoria Bruni, Michela Tartaglione, Domenico Vitulano
Digital Signal Processing (2022) Vol. 128, pp. 103635-103635
Closed Access | Times Cited: 5
A Local Synchrosqueezing Based TFA Post-processing Tool and Application to Bearing Fault Diagnosis
Jingbo Liu, Yabo Wang, Zong Meng
Mechanisms and machine science (2024), pp. 467-479
Closed Access
Seismic data denoising with two-step prediction strategy based on Neural Network
Yongjie Zhang, Bingluo Gu, Zhiguang Sun, et al.
Computers & Geosciences (2024) Vol. 187, pp. 105595-105595
Closed Access
Proportional Chirplet basis transform for rotating machinery vibration signal analysis without prior knowledge
Jingbo Liu, Zong Meng, Dawei Sun, et al.
Mechanical Systems and Signal Processing (2024) Vol. 224, pp. 112027-112027
Closed Access
Non-Sinusoidal micro-Doppler Estimation Based on Dual-Branch Network
Jie Lu, Wenpeng Zhang, Yongxiang Liu, et al.
Remote Sensing (2022) Vol. 14, Iss. 19, pp. 4764-4764
Open Access | Times Cited: 2
Robustness Properties of Local Maximum Synchrosqueezing Transform
Ran Zhang
(2022)
Open Access | Times Cited: 1
High-resolution chirplet transform: from parameters analysis to parameters combination
Xiangxiang Zhu, Bei Li, Zhuosheng Zhang, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 1
Multiple Enhanced Synchrosqueezing in the Time-Frequency-Chirprate Space
Tao Chen, Lei Xie, Mingzhe Cui, et al.
(2023)
Closed Access
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