A fast and accurate time–frequency analysis is challenging for many applications, especially in the current big data era. A recent work introduces a fast continuous wavelet transform that effectively boosts the analysis speed without sacrificing the resolution of the result.
This is a preview of subscription content, access via your institution
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$99.00 per year
only $8.25 per issue
Rent or buy this article
Prices vary by article type
Prices may be subject to local taxes which are calculated during checkout
Daubechies, I. Ten Lectures on Wavelets (USA Society for Industrial and Applied Mathematics, 1992).
Shena, M. J. IEEE Trans. Signal Process. 40, 2464–2482 (1992).
Addison, P. S. Phil. Trans. R. Soc. A 376, 20170258 (2018).
Arts, L. P. A. & van den Broek, E. L. Nat. Comput. Sci. https://doi.org/10.1038/s43588-021-00183-z (2022).
The author declares no competing interests.
About this article
Cite this article
Srivastava, M. Revisiting signal analysis in the big data era. Nat Comput Sci 2, 70–71 (2022). https://doi.org/10.1038/s43588-022-00210-7