Concept
Non-uniform discrete Fourier transform
Cours associés (32)
EE-559: Deep learning
This course explores how to design reliable discriminative and generative neural networks, the ethics of data acquisition and model deployment, as well as modern multi-modal models.
MICRO-511: Image processing I
Introduction to the basic techniques of image processing. Introduction to the development of image-processing software and to prototyping using Jupyter notebooks. Application to real-world examples in
MICRO-512: Image processing II
Study of advanced image processing; mathematical imaging. Development of image-processing software and prototyping in Jupyter Notebooks; application to real-world examples in industrial vision and bio
EE-726: Sparse stochastic processes
We cover the theory and applications of sparse stochastic processes (SSP). SSP are solutions of differential equations driven by non-Gaussian innovations. They admit a parsimonious representation in a
PHYS-757: Axiomatic Quantum Field Theory
Presentation of Wightman's axiomatic framework to QFT as well as to the necessary mathematical objects to their understanding (Hilbert analysis, distributions, group representations,...).
Proofs of
COM-500: Statistical signal and data processing through applications
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
EE-406: Fundamentals of electrical circuits and systems I
This course gives you an introduction to signal processing, focusing on the Fourier transform, on signal sampling and reconstruction and the Discrete Fourier transform.
COM-406: Foundations of Data Science
We discuss a set of topics that are important for the understanding of modern data science but that are typically not taught in an introductory ML course. In particular we discuss fundamental ideas an
MATH-202(c): Analysis III
The course studies the fundamental concepts of vector analysis and Fourier-Laplace analysis with a view to their use in solving multidisciplinary problems in scientific engineering.
MATH-205: Analysis IV - Lebesgue measure, Fourier analysis
Learn the basis of Lebesgue integration and Fourier analysis