Wavelet Based Dictionaries for Dimensionality Reduction of ECG Signals


Dimensionality reduction of ECG signals is considered within the framework of sparse representation. The approach constructs the signal model by selecting elementary components from a redundant dictionary via a greedy strategy. The proposed wavelet dictionaries are built from the multiresolution scheme, but translating the prototypes within a shorter step than that corresponding to the wavelet basis. The reduced representation of the signal is shown to be suitable for compression at low level distortion. In that regard, compression results are superior to previously reported benchmarks on the MIT-BIH Arrhythmia data set.

Publication DOI: https://doi.org/10.1016/j.bspc.2019.101593
Divisions: College of Engineering & Physical Sciences > School of Informatics and Digital Engineering > Mathematics
College of Engineering & Physical Sciences
Uncontrolled Keywords: Sparse representation,ECG compression,Wavelet dictionaries,Greedy pursuit strategies
Publication ISSN: 1746-8108
Full Text Link: https://arxiv.o ... /abs/1811.05517
Related URLs: https://www.sci ... 746809419301739 (Publisher URL)
PURE Output Type: Article
Published Date: 2019-09-01
Published Online Date: 2019-07-08
Accepted Date: 2019-06-07
Authors: Rebollo-Neira, Laura (ORCID Profile 0000-0002-7420-8977)
Cerna, Dana



Version: Draft Version

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