2026-07-22T08:54:00Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:3758 2024-03-06T10:29:08Z ddc:004 open_access

A heuristic for sparse signal reconstruction Apostolopoulos, Theofanis Compressive Sampling sparse signal representation l_0 minimisation non-linear programming signal recovery 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. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Theofanis Apostolopoulos 2012 Is Part Of OASIcs, Volume 28, 2012 Imperial College Computing Student Workshop InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.ICCSW.2012.8 urn:nbn:de:0030-drops-37589 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2012.8 eng https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode