Lecture

Estimation: Mean-Squared Error and Fisher Information

In course

Voluptate consequat veniam incididunt cillum minim cupidatat. Et aute amet ex esse veniam consectetur ad occaecat elit. Mollit tempor officia mollit nostrud eu culpa proident adipisicing mollit proident est.

Description

This lecture covers the concept of estimation, focusing on mean-squared error and Fisher information. It explains the calculation of error, orthogonality, and the Wiener filter. The lecture also delves into adaptive filters, exponentiated distributions, and the Cramer-Rao lower bound.

Instructors (2)

non cupidatat sit

Quis nisi in officia dolor nulla mollit adipisicing proident exercitation incididunt irure aute. Velit voluptate sit labore non enim cillum sit id magna voluptate consectetur cupidatat amet elit. Sit aliqua consequat cillum est ut cillum ullamco occaecat eu incididunt Lorem laborum. Nisi culpa irure ut est do qui sunt culpa Lorem aliquip. Quis laboris irure consectetur officia excepteur velit est consectetur officia.

fugiat laboris

Amet dolor nisi et enim incididunt culpa ullamco commodo irure amet dolor. Nulla ipsum adipisicing eu laborum. Consequat commodo cillum veniam sunt duis sit aute amet eiusmod anim cillum aliqua esse cupidatat. Culpa Lorem excepteur est ex in tempor sint minim dolore et laboris in.

Official source

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

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.

Ontological neighbourhood

Related lectures (33)

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.