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Lecture

Discrete Fourier Transform: Unlimited Duration Signals

In course

EE-350: Signal processing

Dans ce cours, nous présentons les méthodes de base du traitement des signaux. ...

Description

This lecture covers the Discrete Fourier Transform (DFT) applied to signals of unlimited duration. It introduces the concept of limiting signal duration using rectangular windows and discusses the quality of the approximation. The lecture also explores the use of different windows, such as the parabolic and generalized Hamming windows, to improve the accuracy of the DFT. Additionally, it delves into the choice of window length to achieve the desired frequency resolution. Overall, the instructor provides insights into the practical aspects of applying DFT to signals with unlimited duration.

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Instructors (2)

Pascal Frossard

Jean-Philippe Thiran

Jean-Philippe Thiran was born in Namur, Belgium, in August 1970. He received the Electrical Engineering degree and the PhD degree from the Université catholique de Louvain (UCL), Louvain-la-Neuve, Belgium, in 1993 and 1997, respectively. From 1993 to 1997, he was the co-ordinator of the medical image analysis group of the Communications and Remote Sensing Laboratory at UCL, mainly working on medical image analysis. Dr Jean-Philippe Thiran joined the Signal Processing Institute (ITS) of the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland, in February 1998 as a senior lecturer. He was promoted to Assistant Professor in 2004, to Associate Professor in 2011 and is now a Full Professor since 2020. He also holds a 20% position at the Department of Radiology of the University of Lausanne (UNIL) and of the Lausanne University Hospital (CHUV) as Associate Professor ad personam. Dr Thiran's current scientific interests include Computational medical imaging: acquisition, reconstruction and analysis of imaging data, with emphasis on regularized linear inverse problems (compressed sensing, convex optimization). Applications to medical imaging: diffusion MRI, ultrasound imaging, inverse planning in radiotherapy, etc.Computer vision & machine learning: image and video analysis, with application to facial expression recognition, eye tracking, lip reading, industrial inspection, medical image analysis, etc.

Official source

Ontological neighbourhood

Information engineering

Signal processing: Fourier analysis

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