This course teaches the students practical skills needed for solving modern physics problems by means of computation. A number of examples illustrate the utility of numerical computations in various domains of physics.
Cette page est générée automatiquement et peut contenir des informations qui ne sont pas correctes, complètes, à jour ou pertinentes par rapport à votre recherche. Il en va de même pour toutes les autres pages de ce site. Veillez à vérifier les informations auprès des sources officielles de l'EPFL.
Adaptive signal processing, A/D and D/A. This module provides the basic
tools for adaptive filtering and a solid mathematical framework for sampling and
quantization
Prof. Oleg Yazyev (Олег Язев) was born in Simferopol, Crimean peninsula. He obtained his degree in chemistry from Moscow State University in 2003. He then joined Ecole Polytechnique Fédérale de Lausanne (EPFL) completing his PhD thesis in chemistry and chemical engineering in 2007. Next two years he has spent as a postdoctoral fellow at the Institute of Theoretical Physics (ITP) and the Institute for Numerical Research in the Physics of Materials (IRRMA) of the same institution. In 2009-2011 he was a postdoctoral fellow at the Department of Physics of the University of California, Berkeley and the Lawrence Berkeley National Laboratory. In September 2011 he started an independent research group supported by the Swiss National Science Foundation professorship grant. In 2012 he was awarded an ERC Starting grant. His current research focuses on theoretical and computational physics of the recently discovered Dirac fermion materials with strong emphasis on their prospective technological applications. ResearcherID profile of Oleg Yazyev
Machine learning and data analysis are becoming increasingly central in sciences including physics. In this course, fundamental principles and methods of machine learning will be introduced and practi
Building up on the basic concepts of sampling, filtering and Fourier transforms, we address stochastic modeling, spectral analysis, estimation and prediction, classification, and adaptive filtering, w
Anim elit excepteur consectetur nisi sint laborum deserunt nostrud consequat culpa ea eu sunt dolor. Ullamco ullamco laborum excepteur deserunt tempor sit amet elit culpa reprehenderit irure deserunt. Elit est veniam aliqua incididunt fugiat est culpa minim. Et pariatur minim dolore adipisicing officia elit in veniam. Duis id incididunt nostrud ad duis anim aliquip qui occaecat consequat in sint id et.
Amet nulla aliqua nostrud esse incididunt irure laboris. Cupidatat tempor incididunt duis commodo deserunt ad incididunt enim. Reprehenderit tempor pariatur amet culpa voluptate excepteur ad consequat. Ad reprehenderit nulla deserunt nostrud eiusmod laborum aliqua labore. Minim ut reprehenderit irure Lorem et exercitation sunt laborum id sit consequat qui. Excepteur irure minim commodo occaecat consectetur adipisicing adipisicing sint elit nulla non enim laboris anim. Dolore in non eu et veniam cillum laborum ipsum mollit exercitation occaecat minim.
Reprehenderit et eiusmod esse dolore enim non do quis officia. Eu culpa minim mollit sunt cillum dolor qui ex eu in irure. In veniam deserunt et ad sint nisi consectetur veniam anim.
Laboris id consectetur ut quis do cupidatat nostrud ut et duis in. Dolore ad exercitation laboris est qui aliquip laboris dolore in tempor qui excepteur. Officia nisi veniam incididunt elit ipsum eu pariatur nisi.
Aliqua nostrud duis in duis aliquip incididunt elit irure esse. Sint aliquip pariatur eiusmod elit occaecat qui. Labore ea tempor id minim. Officia officia do irure velit ut nulla proident sunt Lorem magna dolor.
