Lecture

Spectral Estimation: Gaussian vs Binary Signals

Description

This lecture covers the spectral estimation problem for Gaussian and binary signals, focusing on the spiked matrix estimation problem. It discusses the computation of mean-squared error, self-consistent equations, and the performance of principal component analysis. The lecture also explores the impact of signal-to-noise ratio on the solutions, the transition between recovery phases, and the use of damping in iterations for convergence.

Instructors (2)

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Official source

https://mediaspace.epfl.ch/media/0_g97igaec

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Ontological neighbourhood

Information engineering

Signal processing: Digital image processing

Statistics

Data analysis: Regression analysis

Mathematics

Analysis: Numerical analysis

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