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A new ECG data compression method based on adaptive vector quantization and residual error compensation

机译:一种新的基于自适应矢量量化和残差误差补偿的ECG数据压缩方法

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In the last few years, data compression has become essential for both storage and transmission especially in the biomedical domain. In this paper, we propose a new technique for the electrocardiogram data compression. It is based on the singular value decomposition and a new adaptive vector quantization. In the proposed method, the codebook is generated adaptively at each quantization stage. The result of this procedure is a reduction of the codebook size. A residual encoding and a compensation of the residual reconstruction error technique are also proposed. Consequently, low reconstruction error was obtained. The technique was tested using arrhythmia database of the Massachusetts Institute of Technology-Beth Israel Hospital and compared to several existing methods. The obtained results were very satisfactory, since a compression ratio of 102.54 was reached for a low reconstruction error.
机译:在过去的几年中,数据压缩对于储存和传输,特别是在生物医学领域中是必不可少的。在本文中,我们提出了一种用于心电图数据压缩的新技术。它基于奇异值分解和新的自适应矢量量化。在所提出的方法中,码本在每个量化阶段自适应地生成。此过程的结果是减少码本大小。还提出了残余编码和残余重建误差技术的补偿。因此,获得了低重建误差。该技术使用Massachusetts Technology-Beth以色列医院的Massachusetts研究所的心律失常数据库进行了测试,并与几种现有方法进行了相比。获得的结果非常令人满意,因为达到了低重建误差的压缩比为102.54。

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