Affiliation:
1. Department of Computer Science, Suny Fredonia, Fredonia, NY 14063,
Abstract
In this work, we investigate the lossless and near-lossless compression of electrocardiogram (ECG) signals with different block-sorting transformations. We show that transformations with smaller context depths are a better choice for ECG signal compression when speed and memory utilization are considered. Further, we show that compression results of our proposed technique is better than other well known techniques, such as bzip2, gzip, and the shorten waveform coder.
Subject
Hardware and Architecture,Theoretical Computer Science,Software
Cited by
4 articles.
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