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首页> 外文期刊>Journal of Communications Technology and Electronics >DPCM Quantizer Adaptation Method for Efficient ECG Signal Compression
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DPCM Quantizer Adaptation Method for Efficient ECG Signal Compression

机译:高效ECG信号压缩的DPCM量化器自适应方法

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This paper addresses the problem of electrocardiogram (ECG) signal compression with the goal to provide a simple compression method that outperforms previously proposed methods. Starting with the study of the ECG signal nature, the manner has been found to optimize rate-quality ratio of the ECG signal by means of differential pulse code modulation (DPCM) and subframe after subframe procession. Particularly, the proposed method includes two kinds of adaptations, short-time and long-time adaptations. The switched quantization i.e. the short-time DPCM quantizer range adaptation is performed according to the statistics of the ECG signal within particular subframes. It is ascertained that the short-time adaptation enables a sophisticated compression control as well as a constant quality of the ECG signal in both segments of low amplitude and high amplitude dynamics. In addition, by grouping the subframes of a particular frame into two groups according to their dynamics and performing the long-time DPCM quantizer range adaptation, based on the statistics of the groups, it has been revealed that an important quality gain is achieved with an insignificant rate increase. Moreover, the two iterative approaches proposed in the paper, mainly differ in the fact whether the long-time range adaptations of the used DPCM quantizers are performed according to the maximum amplitudes or according to the average powers of the signal difference determined in all subframes within a certain group. The benefits of both approaches to the above proposed method are shown and discussed in the paper.
机译:本文旨在解决心电图(ECG)信号压缩问题,目的是提供一种优于先前提出的方法的简单压缩方法。从对ECG信号性质的研究开始,已经发现了通过差分脉冲编码调制(DPCM)和子帧处理后的子帧来优化ECG信号的速率质量比的方法。特别地,所提出的方法包括两种适配,即短时适配和长时间适配。根据特定子帧内的ECG信号的统计来执行切换量化,即,短时DPCM量化器范围自适应。可以确定的是,短时自适应可以在低振幅和高振幅动态两个部分中实现复杂的压缩控制以及ECG信号的恒定质量。此外,通过根据特定帧的动态将其分为两类并进行长时间的DPCM量化器范围自适应,基于各组的统计信息,可以发现,利用率微不足道的增加。此外,本文提出的两种迭代方法的主要区别在于,是根据最大幅度还是根据在所有子帧内确定的信号差的平均功率来执行所使用的DPCM量化器的长时间范围自适应。某个群体。本文展示并讨论了上述方法的两种方法的好处。

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