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Transient signals are often composed of a series of modes that have multivalued time-dependent instantaneous frequency (IF), which brings challenges to the development of signal processing technology. Fortunately, the group delay (GD) of…

Signal Processing · Electrical Eng. & Systems 2022-02-23 Haoran Dong , Gang Yu

Analysis of signals with oscillatory modes with crossover instantaneous frequencies is a challenging problem in time series analysis. One way to handle this problem is lifting the 2-dimensional time-frequency representation to a…

Numerical Analysis · Mathematics 2022-06-22 Ziyu Chen , Hau-Tieng Wu

High-resolution time-frequency (TF) analysis plays crucial role in characterizing multicomponent signal (MCSs) and estimating oscillatory properties. Linear time-frequency representations (TFRs) such as classical short-time Fourier…

Signal Processing · Electrical Eng. & Systems 2023-12-12 Rayyan Abdalla

Recently the study of modeling a non-stationary signal as a superposition of amplitude and frequency-modulated Fourier-like oscillatory modes has been a very active research area. The synchrosqueezing transform (SST) is a powerful method…

Numerical Analysis · Mathematics 2018-12-31 Haiyan Cai , Qingtang Jiang , Lin Li , Bruce W. Suter

In many applications, it is necessary to retrieve the sub-signal building blocks of a multi-component signal, which is usually non-stationary in real-world and real-life applications. Empirical mode decomposition (EMD), synchrosqueezing…

Numerical Analysis · Mathematics 2022-05-30 Charles K. Chui , Qingtang Jiang , Lin Li , Jian Lu

The synchrosqueezing transform, a kind of reassignment method, aims to sharpen the time-frequency representation and to separate the components of a multicomponent non-stationary signal. In this paper, we consider the short-time Fourier…

Signal Processing · Electrical Eng. & Systems 2019-09-27 Lin Li , Haiyan Cai , Hongxia Han , Qingtang Jiang , Hongbing Ji

In nature and engineering world, the acquired signals are usually affected by multiple complicated factors and appear as multicomponent nonstationary modes. In such and many other situations, it is necessary to separate these signals into a…

Signal Processing · Electrical Eng. & Systems 2021-10-14 Lin Li , Ningning Han , Qingtang Jiang , Charles K. Chui

The synchrosqueezing transform (SST) was developed recently to separate the components of non-stationary multicomponent signals. The continuous wavelet transform-based SST (WSST) reassigns the scale variable of the continuous wavelet…

Signal Processing · Electrical Eng. & Systems 2020-08-26 Jian Lu , Qingtang Jiang , Lin Li

Resonance frequencies can provide useful information on the deformation occurring during fracturing experiments or $CO_2$ management, complementary to the microseismic event distribution. An accurate time-frequency representation is of…

Geophysics · Physics 2013-01-08 Roberto H. Herrera , Jean-Baptiste Tary , Mirko van der Baan

Recent advances in the chirplet transform and wavelet-chirplet transform (WCT) have enabled the estimation of instantaneous frequencies (IFs) and chirprates, as well as mode retrieval from multicomponent signals with crossover IF curves.…

Signal Processing · Electrical Eng. & Systems 2025-08-26 Qingtang Jiang , Shuixin Li , Jiecheng Chen , Lin Li

This study focuses on the analysis of signals containing multiple components with crossover instantaneous frequencies (IF). This problem was initially solved with the chirplet transform (CT). Also, it can be sharpened by adding the…

Numerical Analysis · Mathematics 2024-05-14 Yi-Ju Yen , De-Yan Lu , Sing-Yuan Yeh , Jian-Jiun Ding , Chun-Yen Shen

This paper proposes a Time-Frequency Space Transformation (TFST) to derive non-orthogonal bases for modulation techniques over the delay-doppler plane. A family of Overloaded Delay-Doppler Modulation (ODDM) techniques is proposed based on…

Information Theory · Computer Science 2024-02-07 Mahdi Shamsi , Farokh Marvasti

The continuous wavelet transform (CWT) is a linear time-frequency representation and a powerful tool for analyzing non-stationary signals. The synchrosqueezing transform (SST) is a special type of the reassignment method which not only…

Signal Processing · Electrical Eng. & Systems 2019-09-27 Lin Li , Haiyan Cai , Qingtang Jiang

The objective of this paper is to introduce an innovative approach for the recovery of non-stationary signal components with possibly cross-over instantaneous frequency (IF) curves from a multi-component blind-source signal. The main idea…

Numerical Analysis · Mathematics 2020-12-29 Charles K. Chui , Qingtang Jiang , Lin Li , Jian Lu

Time-frequency analysis (TFA) techniques play an important role in the field of machine fault diagnosis attributing to their superiority in dealing with nonstationary signals. Synchroextracting transform (SET) and transient-extracting…

Signal Processing · Electrical Eng. & Systems 2024-02-09 Yunlong Ma , Gang Yu , Tianran Lin , Qingtang Jiang

Synchrosqueezing transform (SST) is a useful tool for vibration signal analysis due to its high time-frequency (TF) concentration and reconstruction properties. However, existing SST requires much processing time for large-scale data. In…

Signal Processing · Electrical Eng. & Systems 2020-03-17 Dong He , Hongrui Cao

The interest in deep learning methods for solving traditional signal processing tasks has been steadily growing in the last years. Time delay estimation (TDE) in adverse scenarios is a challenging problem, where classical approaches based…

Audio and Speech Processing · Electrical Eng. & Systems 2020-02-04 Luca Comanducci , Maximo Cobos , Fabio Antonacci , Augusto Sarti

Recently the synchrosqueezed transform (SST) was developed as an empirical mode decomposition (EMD)-like tool to enhance the time-frequency resolution and energy concentration of a multi-component non-stationary signal and provides more…

Numerical Analysis · Mathematics 2020-12-29 Charles K. Chui , Qingtang Jiang , Lin Li , Jian Lu

Low-channel EEG devices are crucial for portable and entertainment applications. However, the low spatial resolution of EEG presents challenges in decoding low-channel motor imagery. This study introduces TSFF-Net, a novel network…

Machine Learning · Computer Science 2023-04-05 Zhengqing Miao , Meirong Zhao

In nature, signals often appear in the form of the superposition of multiple non-stationary signals. The overlap of signal components in the time-frequency domain poses a significant challenge for signal analysis. One approach to addressing…

Signal Processing · Electrical Eng. & Systems 2025-10-14 Shuixin Li , Jiecheng Chen , Qingtang Jiang , Jian Lu
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