Wavelets

Mathieu wavelet

The Mathieu equation is a linear second-order differential equation with periodic coefficients. The French mathematician, E. Léonard Mathieu, first introduced this family of differential equations, nowadays termed Mathieu equations, in his “Memoir on vibrations of an elliptic membrane” in 1868. "Mathieu functions are applicable to a wide variety of physical phenomena, e.g., diffraction, amplitude distortion, inverted pendulum, stability of a floating body, radio frequency quadrupole, and vibration in a medium with modulated density" (Wikipedia).

Mathieu wavelet
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Stéphane Jaffard: From function spaces to stylometry: the wavelet bridge

Find this video and other talks given by worldwide mathematicians on CIRM's Audiovisual Mathematics Library: http://library.cirm-math.fr. And discover all its functionalities: - Chapter markers and keywords to watch the parts of your choice in the video - Videos enriched with abstracts, b

From playlist 30 years of wavelets

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An introduction to the wavelet transform (and how to draw with them!)

The wavelet transform allows to change our point of view on a signal. The important information is condensed in a smaller space, allowing to easily compress or filter the signal. A lot of approximations are made in this video, like a lot of missing √2 factors. This choice was made to keep

From playlist Summer of Math Exposition Youtube Videos

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Wavelets: a mathematical microscope

Wavelet transform is an invaluable tool in signal processing, which has applications in a variety of fields - from hydrodynamics to neuroscience. This revolutionary method allows us to uncover structures, which are present in the signal but are hidden behind the noise. The key feature of w

From playlist Fourier

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Journées Hénon - 10/21 - Thibault Damour

Chaos in classical and quantum cosmological billiards

From playlist Michel Hénon Memoriam

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Inauguration de la Maison de chercheurs Jean-Morlet

La Maison de chercheurs Jean-Morlet a été inaugurée au Centre International de rencontres Mathématiques le vendredi 22 mars 2013. Vous pourrez entendre dans ce film les discours de: Patrick Foulon, directeur du CIRM Dominique Léger, Vice-président de la Fondation du Patrimoine, François T

From playlist Interviews en français - French interviews

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Stéphane Mallat: "Deep Generative Networks as Inverse Problems"

New Deep Learning Techniques 2018 "Deep Generative Networks as Inverse Problems" Stéphane Mallat, École Normale Supérieure Abstract: Generative Adversarial Networks and Variational Auto-Encoders provide impressive image generations from Gaussian white noise, which are not well understood

From playlist New Deep Learning Techniques 2018

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Learning Multiscale Physics with Deep Neural Networks - Mallat - Workshop 2 - CEB T3 2018

Stephane Mallat (College de France/ENS) / 26.10.2018 Learning Multiscale Physics with Deep Neural Networks ---------------------------------- Vous pouvez nous rejoindre sur les réseaux sociaux pour suivre nos actualités. Facebook : https://www.facebook.com/InstitutHenriPoincare/ Twitte

From playlist 2018 - T3 - Analytics, Inference, and Computation in Cosmology

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Hajar Bahouri - De l'analyse des EDPs non linéaires à la théorie des groupes

Créteil, Prix Paul Doisteau 2016 Réalisation technique : Antoine Orlandi (GRICAD) | Tous droits réservés

From playlist Des mathématiciens primés par l'Académie des Sciences 2017

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Pierre de Fermat: Biography of a Great Thinker

As a mathematician, Pierre de Fermat is known as the "Prince of Amateurs." He was actually a lawyer, but worked on math as a hobby. He helped found probability theory and analytic geometry, and made many contributions to number theory. He is possibly best known for "Fermat's Last Theore

From playlist It Starts With Literacy

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Jean-Claude Risset: Sound, music and wavelets in Marseille: A reminder of early sonic [...]

Find this video and other talks given by worldwide mathematicians on CIRM's Audiovisual Mathematics Library: http://library.cirm-math.fr. And discover all its functionalities: - Chapter markers and keywords to watch the parts of your choice in the video - Videos enriched with abstracts, b

From playlist 30 years of wavelets

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Interview Pascal Hubert

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From playlist Interviews en français - French interviews

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Understanding Wavelets, Part 1: What Are Wavelets

This introductory video covers what wavelets are and how you can use them to explore your data in MATLAB®. •Try Wavelet Toolbox: https://goo.gl/m0ms9d •Ready to Buy: https://goo.gl/sMfoDr The video focuses on two important wavelet transform concepts: scaling and shifting. The concepts ca

From playlist Understanding Wavelets

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Glen Evenbly: "Using tensor networks to design improved wavelets for image compression"

Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021 Workshop II: Tensor Network States and Applications "Using tensor networks to design improved wavelets for image compression" Glen Evenbly - Georgia Institute of Technology, Physics Abstract: Tensor networks

From playlist Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021

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Wavelets and Multiresolution Analysis

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From playlist Data-Driven Science and Engineering

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Morlet wavelets in time and in frequency

Convolution requires two time series: The data and the kernel. The data is what you already have (EEG/MEG/LFP/etc); here you will learn about the most awesomest kernel for time-frequency decomposition of neural time series data: The Morlet wavelet. The video uses files you can download fr

From playlist OLD ANTS #3) Time-frequency analysis via Morlet wavelet convolution

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Stéphane Mallat: A Wavelet Zoom to Analyze a Multiscale World

Abstract: Complex physical phenomena, signals and images involve structures of very different scales. A wavelet transform operates as a zoom, which simplifies the analysis by separating local variations at different scales. Yves Meyer found wavelet orthonormal bases having better propertie

From playlist Abel Lectures

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Understanding Wavelets, Part 2: Types of Wavelet Transforms

Explore the workings of wavelet transforms in detail. •Try Wavelet Toolbox: https://goo.gl/m0ms9d •Ready to Buy: https://goo.gl/sMfoDr You will also learn important applications of using wavelet transforms with MATLAB®. Video Transcript: In the previous session, we discussed wavelet co

From playlist Understanding Wavelets

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Effects of Morlet wavelet parameters on results

There is one important parameter of Morlet wavelets, which is the width of the Gaussian (a.k.a. the "number of cycles"). In this video we will explore this parameter and see what effects different parameter values have on the results. I will also provide some advice for when you should use

From playlist OLD ANTS #3) Time-frequency analysis via Morlet wavelet convolution

Related pages

Wavelet | Cascade algorithm | Multiresolution analysis | Mathieu function