Improved Simultaneous Matching Pursuit for Multi-lead ECG Data Compression

In this paper, we describe an algorithm to decompose multi-lead ECG data simultaneously into different linear expansions of the same atoms that are selected from a redundant dictionary. These waveforms are chosen in order to best match the signal structures. The proposed approach is a modification to the Simultaneous Orthogonal Matching Pursuit (SMP), and it is a general procedure to compute adaptive multiple signals representations with a dictionary, a combination of Hermite functions and Gabor functions. By comparison to SMP, much less atoms are selected to present signals in our algorithm, since two adjacent atoms will be replaced by their optimal compounding if some condition is satisfied. Therefore, the compression ratio of Multi-ECG can achieve better performance by our method than SMP.