Intrinsic time-scale decomposition: time–frequency–energy analysis and real-time filtering of non-stationary signals

By Mark G. Frei, Ivan Osorio. Proceedings of the Royal Society A, 2007

394 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Control and Systems Engineering, Geophysics

View Paper: https://www.semanticscholar.org/paper/fb036d7eee3ddd5128bb8898c49e9a1eb65c0890

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Dongxiang Jiang
2. Chao Liu
3. Jie Chen
4. Xueli An

In Control and Systems Engineering

1. Dongxiang Jiang
2. Chao Liu
3. Satish T. S. Bukkapatnam
4. Jie Chen
5. Xueli An

In Geophysics

1. Dongxiang Jiang
2. Chao Liu
3. Jie Chen
4. Xueli An

Citations in the corpus

• Application of the intrinsic time-scale decomposition method to fault diagnosis of wind turbine bearing (2012, methodology): “The intrinsic time-scale decomposition (ITD) method can decompose a complex signal into several proper rotation components and extract the dynamic features of non-stationary signals accurately (Frei and Osorio, 2007).”
• Time series forecasting for nonlinear and non-stationary processes: a review and comparative study (2015, background): “Functional decomposition models (Frei and Osorio, 2007) for time series forecasting have received increased attention in recent years.”