mlsanityData to 14 Oct 2026

Empirical wavelet transform

arXiv 2410.23534 ↗First posted 31 Oct 2024math.FA eess.SPcited by 6

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Abstract (arXiv)

Some recent methods, like the Empirical Mode Decomposition (EMD), propose to decompose a signal accordingly to its contained information. Even though its adaptability seems useful for many applications, the main issue with this approach is its lack of theory. This paper presents a new approach to build adaptive wavelets. The main idea is to extract the different modes of a signal by designing an appropriate wavelet filter bank. This construction leads us to a new wavelet transform, called the empirical wavelet transform. Many experiments are presented showing the usefulness of this method compared to the classic EMD.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 31 Oct 2024.

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Citing papers per year: 2024: 1; 2025: 4; 2026: 1.

6 papers.