Français
4. Optimum filtering
4.1 Problem position
The term optimal filtering means that filter design is not based on frequency or time specifications, but refers to a criterion such as mean square error.
Consequently, the aim of optimal linear filtering is to find the "best" linear filter, i.e. the one that provides an approximation such that the mean square error is minimal.
Common applications include noise reduction, prediction, inverse filtering, identification, detection coding and more.
One of the most important optimal filters in linear estimation is the Wiener filter.
The Ultimate Scientific and Technical Reference
This article is included in
Electronic measurements and tests
This offer includes:
Knowledge Base
Updated and enriched with articles validated by our scientific committees
Services
A set of exclusive tools to complement the resources
Practical Path
Operational and didactic, to guarantee the acquisition of transversal skills
Doc & Quiz
Interactive articles with quizzes, for constructive reading
Optimum filtering
Kalman filtering
Bibliography
Directory
Laboratories – Design offices – Schools – Research centers (non-exhaustive list)
MATLAB 2019 – R2019b Compagnie Mathworks France
https://fr.mathworks.com/products/new_products/release2019b.html
The Ultimate Scientific and Technical Reference
