Lecture

Extended Kalman Filter

In course

Ullamco ad ullamco elit duis commodo aliquip qui aliqua qui deserunt ullamco minim id ea. Irure sunt nulla id ex in laborum aliqua. In culpa duis exercitation officia non duis voluptate consequat veniam. Consectetur enim esse laboris eu consequat.

Description

This lecture covers the Extended Kalman Filter (EKF) algorithm, focusing on time-correlated observations and practical implementations. Topics include state transition equations, observation equations, covariance matrices, Kalman gain computation, and invertibility conditions.

This video is available exclusively on Mediaspace for a restricted audience. Please log in to MediaSpace to access it if you have the necessary permissions.

Watch on Mediaspace

Instructor

ipsum elit

Excepteur duis in aliquip enim nostrud non quis dolor. Consectetur ex deserunt excepteur laboris ullamco cillum excepteur. Cupidatat consectetur mollit non culpa ad. Non et sit culpa reprehenderit eiusmod nostrud proident cillum occaecat eu reprehenderit. Commodo nostrud proident dolore elit eiusmod consectetur nostrud pariatur nostrud ullamco cillum qui. Lorem dolore occaecat pariatur amet amet exercitation ut do eiusmod nisi incididunt reprehenderit commodo ea.

Official source

https://mediaspace.epfl.ch/media/0_zzs0yv9a

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related lectures (31)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.