Inspired by the use of adaptive kernel-based Cohen's class time-frequency distributions (CCTFDs) for cross-term suppression, this paper aims to explore novel adaptive kernel functions for denoising. We integrate Wiener filter principle and the time-frequency filtering mechanism of CCTFD to design the least-squares adaptive filter method in the Wigner-Ville distribution (WVD) domain, giving birth to the least-squares adaptive filter-based CCTFD whose kernel function can be adjusted with the input signal automatically to achieve the minimum mean-square error denoising in the WVD domain. Some examples are also carried out to demonstrate that the proposed adaptive CCTFD outperforms some state-of-the-arts in noise suppression.
@article{arxiv.2408.04210,
title = {Adaptive Cohen's Class Time-Frequency Distribution},
author = {Manjun Cui and Zhichao Zhang},
journal= {arXiv preprint arXiv:2408.04210},
year = {2025}
}