A heuristic for sparse signal reconstruction

Apostolopoulos, Theofanis

doi:10.4230/OASIcs.ICCSW.2012.8

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A heuristic for sparse signal reconstruction

Author Theofanis Apostolopoulos

Part of: Volume: 2012 Imperial College Computing Student Workshop (ICCSW 2012)
Part of: Series: Open Access Series in Informatics (OASIcs)
License: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported license
Publication Date: 2012-11-09

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Document Identifiers

DOI: 10.4230/OASIcs.ICCSW.2012.8
URN: urn:nbn:de:0030-drops-37589

Subject Classification

Keywords

Compressive Sampling
sparse signal representation
l_0 minimisation
non-linear programming
signal recovery

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Abstract

Compressive Sampling (CS) is a new method of signal acquisition and reconstruction from frequency data which do not follow the basic principle of the Nyquist-Shannon sampling theory. This new method allows reconstruction of the signal from substantially fewer measurements than those required by conventional sampling methods. We present and discuss a new, swarm based, technique for representing and reconstructing signals, with real values, in a noiseless environment. The method consists of finding an approximation of the l_0-norm based problem, as a combinatorial optimization problem for signal reconstruction. We also present and discuss some experimental results which compare the accuracy and the running time of our heuristic to the IHT and IRLS methods.

Cite As Get BibTex

Theofanis Apostolopoulos. A heuristic for sparse signal reconstruction. In 2012 Imperial College Computing Student Workshop. Open Access Series in Informatics (OASIcs), Volume 28, pp. 8-14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012) https://doi.org/10.4230/OASIcs.ICCSW.2012.8

Author Details

Theofanis Apostolopoulos

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