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Zooming into Precision: The Zoom TFD for High-Resolution Analysis of Non-Stationary Signals
Author(s) -
Nisreen Said Amer,
Samir Brahim Belhaouari
Publication year - 2025
Publication title -
ieee access
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 0.587
H-Index - 127
eISSN - 2169-3536
DOI - 10.1109/access.2025.3574237
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
This paper introduces Zoom TFD, a time-frequency decomposition (TFD) method designed for the high-resolution analysis of non-stationary signals, achieving optimal energy concentration, high time-frequency resolution, and inherent cross-term suppression. Traditional TFDs, such as the Wigner-Ville Distribution (WVD) and Choi-Williams Distribution (CWD), often struggle with resolution trade-offs and cross-term interference, while methods like Zhao-Atlas-Marks Distribution (ZAMD) attempt to mitigate these effects at the cost of higher computational complexity. Zoom TFD takes a different approach, integrating adaptive Fourier Transform windowing with a minimization-based spectral selection mechanism. This formulation enables the dynamic refinement of the time-frequency representation by selectively enhancing dominant spectral components while suppressing noise and unwanted harmonics, ensuring a more precise and focused analysis. The effectiveness of the Zoom TFD is assessed against ten leading state-of-the-art TFDs using the Boashash–Sucic Normalized Instantaneous Resolution and Heisenberg uncertainty performance measures. This evaluation is conducted across a variety of experimental and simulated signals, such as frequency-modulated chirps and multi-component signals. The results indicate that the Zoom Time-Frequency Distribution (TFD) consistently outperforms existing methods. It achieves the highest energy concentration and the lowest uncertainty, demonstrating its robustness for precise and interference-free time-frequency analysis. This work establishes the Zoom TFD as a powerful tool for signal analysis, setting a new benchmark for high-resolution time-frequency representation applications, ranging from biomedical engineering to communications.

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