Wave-shape oscillatory model for nonstationary periodic time series analysis
Article Properties
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DOI (url)
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Publication Date2021/01/01
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Journal
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Indian UGC (journal)
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Refrences61
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Citations12
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Yu-Ting Lin
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John Malik
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Hau-Tieng Wu
Cite
Lin, Yu-Ting, et al. “Wave-Shape Oscillatory Model for Nonstationary Periodic Time Series Analysis”. Foundations of Data Science, vol. 3, no. 2, 2021, p. 99, https://doi.org/10.3934/fods.2021009.
Lin, Y.-T., Malik, J., & Wu, H.-T. (2021). Wave-shape oscillatory model for nonstationary periodic time series analysis. Foundations of Data Science, 3(2), 99. https://doi.org/10.3934/fods.2021009
Lin, Yu-Ting, John Malik, and Hau-Tieng Wu. “Wave-Shape Oscillatory Model for Nonstationary Periodic Time Series Analysis”. Foundations of Data Science 3, no. 2 (2021): 99. https://doi.org/10.3934/fods.2021009.
Lin YT, Malik J, Wu HT. Wave-shape oscillatory model for nonstationary periodic time series analysis. Foundations of Data Science. 2021;3(2):99.
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
Non-Parametric and Adaptive Modelling of Dynamic Periodicity and Trend with Heteroscedastic and Dependent Errors | Journal of the Royal Statistical Society Series B: Statistical Methodology |
| 71 | 2013 |
| Recycling cardiogenic artifacts in impedance pneumography | Biomedical Signal Processing and Control |
| 8 | 2019 |
| 10.1201/b13568 | ||||
Extracting a shape function for a signal with intra-wave frequency modulation | Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences |
| 20 | 2016 |
| 10.1161/01.CIR.0000105767.94169.E3 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Removal of electrical stimulus artifact in local field potential recorded from subthalamic nucleus by using manifold denoising | Journal of Neuroscience Methods |
| 2024 | |
| Fully adaptive time-varying wave-shape model: Applications in biomedical signal processing | Signal Processing |
| 2024 | |
Unsupervised ensembling of multiple software sensors with phase synchronization: a robust approach for electrocardiogram-derived respiration | Physiological Measurement |
| 2024 | |
Unsupervised ensembling of multiple software sensors with phase synchronization: a robust approach for electrocardiogram-derived respiration | Physiological Measurement |
| 2024 | |
| Arterial blood pressure waveform in liver transplant surgery possesses variability of morphology reflecting recipients’ acuity and predicting short term outcomes | Journal of Clinical Monitoring and Computing |
| 2023 |
Citations Analysis
The category
Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks 5
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Decomposing Non-Stationary Signals With Time-Varying Wave-Shape Functions and was published in 2021. The most recent citation comes from a 2024 study titled Unsupervised ensembling of multiple software sensors with phase synchronization: a robust approach for electrocardiogram-derived respiration. This article reached its peak citation in 2023, with 5 citations. It has been cited in 10 different journals. Among related journals, the Physiological Measurement cited this research the most, with 2 citations. The chart below illustrates the annual citation trends for this article.