Signal Analysis using Born-Jordan-type Distribution
Elena Cordero, Maurice de Gosson, Monika D\"orfler, Fabio Nicola
TL;DR
This paper reviews recent advances in signal analysis using Cohen class time-frequency distributions, highlighting their effectiveness in reducing artefacts and discussing their properties, drawbacks, and open problems.
Contribution
It introduces new Cohen class distributions generalizing the Wigner distribution and analyzes their properties and limitations in signal analysis.
Findings
Effective in damping artefacts in signals
Survey of properties and drawbacks of Cohen class distributions
Identification of open problems in the field
Abstract
In this note we exhibit recent advances in signal analysis via time-frequency distributions. New members of the Cohen class, generalizing the Wigner distribution, reveal to be effective in damping artefacts of some signals. We will survey their main properties and drawbacks and present open problems related to such phenomena.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsImage and Signal Denoising Methods · Machine Fault Diagnosis Techniques · Control Systems and Identification