WVDNet: Time-frequency analysis via semi-supervised learning

N Liu, J Wang, Y Yang, Z Li… - IEEE Signal Processing …, 2023 - ieeexplore.ieee.org
The bilinear based method is one of the commonly used tools in time-frequency analysis
(TFA) fields. However, it suffers from the trade-off of high resolution and cross-term …

Crossterm-free time-frequency representation exploiting deep convolutional neural network

S Zhang, MSR Pavel, YD Zhang - Signal Processing, 2022 - Elsevier
Bilinear time-frequency (TF) analyses provide high-resolution time-varying frequency
characterization of nonstationary signals. However, because of their bilinear natures, such …

[LIVRE][B] Strategies for Sparsity-Based Time-Frequency Analyses

S Zhang - 2021 - search.proquest.com
Nonstationary signals are widely observed in many real-world applications, eg, radar, sonar,
radio astronomy, communication, acoustics, and vibration applications. Joint time-frequency …

[PDF][PDF] Crossterm-Free Time-Frequency Representation Exploiting Deep Convolutional Neural Network

MSRP Shuimei Zhang, YD Zhang - yiminzhang.com
Bilinear time-frequency (TF) analyses provide high-resolution time-varying frequency
characterization of nonstationary signals. However, because of their bilinear natures, such …

[CITATION][C] Strategies for Removing Non-stationary Effects in Machine Diagnostics using Model-driven and Artificial Intelligence Techniques

MD Choudhury - 2021 - ResearchSpace@ Auckland