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A comparative study of adaptive algorithms for ECG data compression using Hermite models

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2 Author(s)
Jane, R. ; Inst. de Cibernetica, CSIC, Barcelona, Spain ; Olmos, S.

Modeling of signals using Hermite functions is a very appropriate technique for ECG data compression. ECG signal can be highly nonstationary in ambulatory monitoring or during stress test. Adaptive algorithms with a fast convergence are necessary, when data compression of nonstationary signals must be performed. Here, the authors analyse several adaptive algorithms that improves the behaviour of classical least mean squares

Published in:

Engineering in Medicine and Biology Society, 1994. Engineering Advances: New Opportunities for Biomedical Engineers. Proceedings of the 16th Annual International Conference of the IEEE

Date of Conference:

1994