Wavelet Based Dictionaries for Dimensionality Reduction of ECG Signals

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Abstract

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.
Original languageEnglish
Article number101593
JournalBiomedical Signal Processing and Control
Volume54
Early online date8 Jul 2019
DOIs
Publication statusPublished - 1 Sep 2019

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Keywords

  • Sparse representation
  • ECG compression
  • Wavelet dictionaries
  • Greedy pursuit strategies

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