心电信号压缩感知采样与恢复.doc
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心电信号压缩感知采样与恢复,2.63万字自己原创的毕业论文，仅在本站独家出售，重复率低，推荐下载使用摘要 近年来，由心血管疾病导致的死亡人数在不断增加，而心电图是反映心脏生理活动的一种直观的图形表现形式，它对判断心脏的功能和诊断心脏疾病有着重要的参考依据。因此如何通过压缩来减少需要传输的心电数据数量并利用压缩后数据准确恢...
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心电信号压缩感知采样与恢复
2.63万字
自己原创的毕业论文，仅在本站独家出售，重复率低，推荐下载使用
摘要 近年来，由心血管疾病导致的死亡人数在不断增加，而心电图是反映心脏生理活动的一种直观的图形表现形式，它对判断心脏的功能和诊断心脏疾病有着重要的参考依据。因此如何通过压缩来减少需要传输的心电数据数量并利用压缩后数据准确恢复图像在临床上具有十分重要的意义。
为了便于对大量心电数据进行存储﹑分析﹑传输，则必须对其进行有效地压缩。传统的压缩技术一直遵循奈奎斯特采样定理，由于该定理在采样频率上的限制，越来越满足不了当代的需求。压缩感知理论是一种新型的信号压缩理论，它能对信号进行十分有效地压缩且能准确的恢复原信号，同时它在采样频率上不受奈奎斯特采样定理的限制，大大提高了采样的速率与效率。
本文介绍了压缩感知理论的研究与发展，并将压缩感知理论用于心电信号的压缩与恢复，大大减少了心电信号的观测数据，减少了信号的数据传输﹑分析以及处理等等。同时利用当前压缩感知领域的一种快速算法—正交匹配追踪算法对压缩后信号进行仿真恢复并与原信号进行对比并分析其误差。
本文将压缩感知理论运用到心电信号的压缩处理中，压缩感知理论的压缩能力强，它能够实现在不丢失心电信号重要信息的前提下进行高效压缩，并节省了重构时间，从而给心电信号的压缩提供了新的思路。
关键词：心电信号，压缩感知理论，正交匹配追踪算法
Sampling and Recovery of ECG Signal Based on Compressed Sensing
Abstract In recent years,the number of deaths caused by cardiovascular disease is increasing, The ECG is an intuitive graphical representation reflects the physiological activities of the heart, it has an important reference to the function of the heart and the judgment of heart disease . So how to use compression to reduce the number of ECG data transmission and use compressed data to accurately recover the image has a very important significance in clinic.
In order to storage,analysis and transport the large number of ECG data, it must carry on the compression effectively. The traditional compression techniques have been guided by the Nyquist sampling theorem, since the theorem restrictions on the sampling frequency, can not meet contemporary needs.Compressed sensing theory is a new signal compression theory, it is very effective tor signal compression and it also can restore the original signal accurately,At the same time it is not on the sampling frequency Nyquist sampling theorem restrictions,improving the speed and efficiency of sampling greatly .
This paper introduces the research and development of the theory of compressed sensing, and used the compressed sensing theory for ECG signal, it reducing the observation data of ECG signal greatly,and reduces data transmission signal analysis and processing, etc.At the same time, using a fast algorithm of the compressed sensing domain -- orthogonal matching pursuit algorithm for the compressed signal and analyzed the error of the recovery and the original signal.
In this paper, the theory of compressed sensing applied to ECG compression, the compressed sensing theory compression capability is strong, it can realize high efficient compression without loss important information of ECG signal, and save the reconstruction time, which provides a new way for the compression of ECG signal.
Keywords: ECG signal, compressed sensing, orthogonal matching pursuit
algorithm
目 录
第一章 绪论 1
1.1研究的背景 1
1.2心电信号（ECG）的特点 2
1.3心电信号压缩的必要性 5
1.4 仿真平台 5
1.5本文的主要工作与目标 6
第二章 传统心电数据压缩方法 8
2.1概述 8
2.2压缩方法的性能评价 9
2.3常见的心电信号压缩方法 10
2.4小结 14
第三章 压缩感知理论 15
3.1压缩感知理论的概述 15
3.2传统采样与压缩感知的比较 16
3.3压缩感知理论的主要步骤 17
3.3.1信号的稀疏表示 18
3.3.2测量矩阵 20
3.3.3重构算法 22
3.4压缩感知理论的应用和应用瓶颈 25
第四章 基于压缩感知的心电信号的压缩采样 27
4.1心电信号的获取 27
4.2心电信号压缩采样﹑重构的仿真实验 27
4.3仿真结果与分析 29
第五章 总结与展望 32
致 谢 34
参考文献 35
附录 37
2.63万字
自己原创的毕业论文，仅在本站独家出售，重复率低，推荐下载使用
摘要 近年来，由心血管疾病导致的死亡人数在不断增加，而心电图是反映心脏生理活动的一种直观的图形表现形式，它对判断心脏的功能和诊断心脏疾病有着重要的参考依据。因此如何通过压缩来减少需要传输的心电数据数量并利用压缩后数据准确恢复图像在临床上具有十分重要的意义。
为了便于对大量心电数据进行存储﹑分析﹑传输，则必须对其进行有效地压缩。传统的压缩技术一直遵循奈奎斯特采样定理，由于该定理在采样频率上的限制，越来越满足不了当代的需求。压缩感知理论是一种新型的信号压缩理论，它能对信号进行十分有效地压缩且能准确的恢复原信号，同时它在采样频率上不受奈奎斯特采样定理的限制，大大提高了采样的速率与效率。
本文介绍了压缩感知理论的研究与发展，并将压缩感知理论用于心电信号的压缩与恢复，大大减少了心电信号的观测数据，减少了信号的数据传输﹑分析以及处理等等。同时利用当前压缩感知领域的一种快速算法—正交匹配追踪算法对压缩后信号进行仿真恢复并与原信号进行对比并分析其误差。
本文将压缩感知理论运用到心电信号的压缩处理中，压缩感知理论的压缩能力强，它能够实现在不丢失心电信号重要信息的前提下进行高效压缩，并节省了重构时间，从而给心电信号的压缩提供了新的思路。
关键词：心电信号，压缩感知理论，正交匹配追踪算法
Sampling and Recovery of ECG Signal Based on Compressed Sensing
Abstract In recent years,the number of deaths caused by cardiovascular disease is increasing, The ECG is an intuitive graphical representation reflects the physiological activities of the heart, it has an important reference to the function of the heart and the judgment of heart disease . So how to use compression to reduce the number of ECG data transmission and use compressed data to accurately recover the image has a very important significance in clinic.
In order to storage,analysis and transport the large number of ECG data, it must carry on the compression effectively. The traditional compression techniques have been guided by the Nyquist sampling theorem, since the theorem restrictions on the sampling frequency, can not meet contemporary needs.Compressed sensing theory is a new signal compression theory, it is very effective tor signal compression and it also can restore the original signal accurately,At the same time it is not on the sampling frequency Nyquist sampling theorem restrictions,improving the speed and efficiency of sampling greatly .
This paper introduces the research and development of the theory of compressed sensing, and used the compressed sensing theory for ECG signal, it reducing the observation data of ECG signal greatly,and reduces data transmission signal analysis and processing, etc.At the same time, using a fast algorithm of the compressed sensing domain -- orthogonal matching pursuit algorithm for the compressed signal and analyzed the error of the recovery and the original signal.
In this paper, the theory of compressed sensing applied to ECG compression, the compressed sensing theory compression capability is strong, it can realize high efficient compression without loss important information of ECG signal, and save the reconstruction time, which provides a new way for the compression of ECG signal.
Keywords: ECG signal, compressed sensing, orthogonal matching pursuit
algorithm
目 录
第一章 绪论 1
1.1研究的背景 1
1.2心电信号（ECG）的特点 2
1.3心电信号压缩的必要性 5
1.4 仿真平台 5
1.5本文的主要工作与目标 6
第二章 传统心电数据压缩方法 8
2.1概述 8
2.2压缩方法的性能评价 9
2.3常见的心电信号压缩方法 10
2.4小结 14
第三章 压缩感知理论 15
3.1压缩感知理论的概述 15
3.2传统采样与压缩感知的比较 16
3.3压缩感知理论的主要步骤 17
3.3.1信号的稀疏表示 18
3.3.2测量矩阵 20
3.3.3重构算法 22
3.4压缩感知理论的应用和应用瓶颈 25
第四章 基于压缩感知的心电信号的压缩采样 27
4.1心电信号的获取 27
4.2心电信号压缩采样﹑重构的仿真实验 27
4.3仿真结果与分析 29
第五章 总结与展望 32
致 谢 34
参考文献 35
附录 37
