Daubechies wavelets are such incredibly strange and beautiful objects, particularly for how <i>deviant</i> they are compared to everything you are typically familiar with when you are starting your signal processing journey… if it’s possible for a mathematical construction to be punk, then it would be the Daubechies wavelets.
For those unfamiliar with her work, there's a very approachable lecture on wavelets and their common applications here: <a href="https://www.youtube.com/watch?v=a90kMHY0Uto" rel="nofollow">https://www.youtube.com/watch?v=a90kMHY0Uto</a>.
Here is the full list of this year's awardees:<p><a href="https://new.nsf.gov/honorary-awards/national-medal-science#news-5b7" rel="nofollow">https://new.nsf.gov/honorary-awards/national-medal-science#n...</a><p>(Also includes National Medal of Technology and Innovation.)<p>And if you ever get the chance to hear Daubechies speak, go! She gives very clear and accessible talks, and is also very approachable.
This award is well-deserved!<p>I was inspired by her work in the 2010s and have since used the wavelets to denoise time-series with great success [0]. I believe that learning about wavelet transforms is both beneficial in itself, but also beneficial in understand the ubiquitous Fourier transform.<p>[0]: <a href="https://laurentrdc.xyz/posts/wavelet-filtering.html" rel="nofollow">https://laurentrdc.xyz/posts/wavelet-filtering.html</a>
Almost 40 years after the creation of Daubechies wavelets, I know we should wait a bit before awarding people since we can't always know in advance what would stick as important and what would just be temporary hype, but 40 years is too much IMHO…
Is it accurate to say that wavelets were a promising avenue of research in the 1990s but interest in them has kind of died because they were obsoleted by CNNs?