Lecture

Subspace-based approximations

Description

This lecture covers the concept of subspaces in symmetric functions over L₂[-1, 1], the basis vectors for subspaces in R³, and the approximation problem of finding the best approximation for a vector x in a subspace. It also delves into the least-squares approximation method, discussing orthogonal projections, minimum-norm error, and the orthogonality of the error to the approximation.

In MOOCs (4)

Instructors (3)

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Official source

https://mediaspace.epfl.ch/media/0_eb95g2x1

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