In an increasingly data-driven world, mathematical tools known as wavelets have become an indispensable way to analyze and understand information. Many researchers receive their data in the form of ...

Representing images in ways other than pixels allows for powerful processing. This subject, based on signal processing, requires a mathematical fluency to understand the concepts fully. Many software ...

Physics informed neural networks (PINNs), a type of machine learning approach, can be used to find the solution of differential equations by including all of the physics into the loss function and ...

In many fields of study, from science and engineering to economics and psychology, we need to analyze data so that we can discover underlying patterns and information. A common way of doing this is to ...

Compression of digital holograms allows one to store, transmit, and reconstruct large sets of holographic data. There are many digital image compression methods, and usually wavelets are used for this ...

The French mathematician Yves Meyer, a self-described “nomad” who has made deep contributions to the many subfields through which he has roamed over the past half-century, received the 2017 Abel Prize ...

One cold, snowy day, Ingrid Daubechies saw a wealth of hidden meaning in a confused jumble of wiggly lines. Now Daubechie's wavelets are some of the hottest math around. I was in Montreal at the time, ...

Built upon the ubiquitous Fourier transform, the mathematical tools known as wavelets allow unprecedented analysis and understanding of continuous signals. In an increasingly data-driven world, ...