OASIcs.ICCSW.2012.8.pdf
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A heuristic for sparse signal reconstruction
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2012 Imperial College Computing Student Workshop (ICCSW 2012)
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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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
https://doi.org/10.4230/OASIcs.ICCSW.2012.8
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.
Keywords
- Compressive Sampling
- sparse signal representation
- l_0 minimisation
- non-linear programming
- signal recovery
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