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

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

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

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

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