F
François Auger
Researcher at University of Nantes
Publications - 97
Citations - 4002
François Auger is an academic researcher from University of Nantes. The author has contributed to research in topics: Rotor (electric) & Kalman filter. The author has an hindex of 23, co-authored 89 publications receiving 3241 citations.
Papers
More filters
Journal ArticleDOI
Improving the readability of time-frequency and time-scale representations by the reassignment method
François Auger,Patrick Flandrin +1 more
TL;DR: The reassignment method, first applied by Kodera, Gendrin, and de Villedary (1976) to the spectrogram, is generalized to any bilinear time-frequency or time-scale distribution.
Journal ArticleDOI
Time-Frequency Reassignment and Synchrosqueezing: An Overview
François Auger,Patrick Flandrin,Yu-Ting Lin,Stephen McLaughlin,Sylvain Meignen,Thomas Oberlin,Hau-Tieng Wu +6 more
TL;DR: This article provides a general overview of time-frequency (T-F) reassignment and synchrosqueezing techniques applied to multicomponent signals, covering the theoretical background and applications.
Journal ArticleDOI
Industrial Applications of the Kalman Filter: A Review
François Auger,Mickael Hilairet,Josep M. Guerrero,Eric Monmasson,Teresa Orlowska-Kowalska,Seiichiro Katsura +5 more
TL;DR: The Kalman filter has received a huge interest from the industrial electronics community and has played a key role in many engineering fields since the 1970s, ranging from trajectory estimation, state and parameter estimation for control or diagnosis, data merging, signal processing, and so on.
Time - frequency toolbox for use with MATHLAB
TL;DR: In this article, the authors published a paper under the auspices du Centre National de la Recherche Scientifique (CNRS), France and de la Rice University, USA Reference Record created on 2004-09-07, modified on 2016-08-08
Book ChapterDOI
Time-Frequency Reassignment: From Principles to Algorithms
TL;DR: This chapter discusses time–frequency analysis from a second generation perspective, where what is discussed here essentially builds on the methods that have already been extensively studied and used.