Spectrum Estimation by Sparse Representation of Autocorrelation Function

Adel ZAHEDI  Mohammad-Hossein KAHAEI 

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences  Vol.E95-A  No.7  pp.1185-1186
Publication Date: 2012/07/01
Online ISSN: 1745-1337
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Digital Signal Processing
Keyword: 
sparse representationredundant dictionariesirregular samplingspectrum estimation

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Summary: 
A flexible and computationally efficient method for spectral analysis of sinusoidal signals using the Basis Pursuit De-Noising (BPDN) is proposed. This method estimates a slotted Auto-Correlation Function (ACF) and computes the spectrum as the sparse representation of the ACF in a dictionary of cosine functions. Simulation results illustrate flexibility and effectiveness of the proposed method.