Abstract
Electrocardiogram (ECG) data compression algorithm is needed that will reduce the amount of data to be transmitted, stored and analyzed, but without losing the clinical information content. An example of application of hierarchical neural network structure is described for compression of ECG. signals. Then results of this lossy compression method were compared with two efficient compression methods that are fractal based and wavelet based compressions. © Springer-Verlag Berlin Heidelberg 2003.
Cite
CITATION STYLE
Karlik, B. (2003). Hierarchical neural network based compression of ECG signals. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2657, 371–377. https://doi.org/10.1007/3-540-44860-8_38
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