Publication

Sparse spectral factorization: Unicity and Reconstruction Algorithms

Martin Vetterli
2011
Conference Papers

Abstract

Spectral factorization is a classical tool in signal processing and communications. It also plays a critical role in X-ray crystallography, in the context of phase retrieval. In this work, we study the problem of sparse spectral factorization, aiming to recover a one-dimensional sparse signal from its autocorrelation. We present a sufficient condition for the recovery to be unique, and propose an iterative algorithm that can obtain the original signal (up to a sign change, time-shift and time-reversal). Numerical simulations verify the effectiveness of the proposed algorithm.

Official source

https://infoscience.epfl.ch/entities/publication/161a4009-477f-4b56-9403-c3b8cba1a306

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Martin Vetterli
2011
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/161a4009-477f-4b56-9403-c3b8cba1a306

About this result

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Related publications (13)

Sparse spectral factorization: Unicity and Reconstruction Algorithms

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