Abstract
Electrocardiogram (ECG), as a biological signal that contains important information about the cardiac activities of heart, exhibits chaotic characteristics. Since a clean ECG signal is of vital importance in the diagnosis and analysis of heart diseases, we address the task of extracting ECG for a set of noisy observations. Based on the phase space similarity of ECG, we propose an objective called similarity index which fully describes this similarity. A low-complexity algorithm is presented for the similarity index. Simulation results confirm the effectiveness of the proposed method by making comparisons with conventional benchmarks.
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