Population based ant colony optimization for reconstructing ECG signals
Journal
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Date Issued
2016
Author(s)
Abstract
A population based ant optimization algorithm (PACO) for reconstructing electrocardiogram (ECG) signals is proposed in this paper. In particular, the PACO algorithm is used to find a subset of nonzero positions of a sparse wavelet domain ECG signal vector which is used for the reconstruction of a signal. The proposed PACO algorithm uses a time window for fixing certain decisions of the ants during the run of the algorithm. The optimization behaviour of the PACO is compared with two random search heuristics and several algorithms from the literature for ECG signal reconstruction. Experimental results are presented for ECG signals from the MIT-BIT Arrhythmia database. The results show that the proposed PACO reconstructs ECG signals very successfully. © Springer International Publishing Switzerland 2016.
Event(s)
19th European Conference on Applications of Evolutionary Computation, EvoApplications 2016
Subjects
ECG signals
Population based ACO
Signal reconstruction
Subset selection problem
Description
Porto, 30 March 2016 through 1 April 2016
Type
conference paper