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Differentiable adaptive short-time Fourier transform with respect to the window length (2308.02418v1)

Published 26 Jul 2023 in eess.SP, cs.LG, eess.AS, math.ST, and stat.TH

Abstract: This paper presents a gradient-based method for on-the-fly optimization for both per-frame and per-frequency window length of the short-time Fourier transform (STFT), related to previous work in which we developed a differentiable version of STFT by making the window length a continuous parameter. The resulting differentiable adaptive STFT possesses commendable properties, such as the ability to adapt in the same time-frequency representation to both transient and stationary components, while being easily optimized by gradient descent. We validate the performance of our method in vibration analysis.

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Authors (4)
  1. Maxime Leiber (4 papers)
  2. Yosra Marnissi (5 papers)
  3. Axel Barrau (27 papers)
  4. Mohammed El Badaoui (2 papers)
Citations (9)

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