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Bayesian Compressive Sensing Theory Based on Wavelet Coefficient and the Initial Applications

Abstract

依据传统的奈奎斯特采样定理,采样频率必须大于等于信号最高频率的两倍,才能很好的恢复原始信号。而新近发展和兴起的压缩传感理论则是利用原始信号或图像的稀疏性先验知识,通过合适的优化算法,便可以实现由少量的采样值来对原信号的有效重建。 本研究分析了压缩传感的基本理论和近年来的主要发展情况,并对目前主要的重建算法进行了介绍,尤其着重讨论了基于贝叶斯的压缩传感理论和重建方法。本研究的主要工作体现在以下几个方面: (1)由于原信号能稀疏表示是压缩传感的基础和前提条件,本研究中通过一组模拟实验比较了离散余弦变换、离散傅里叶变换和小波变换对原信号稀疏表示的有效性,并以一个稀疏性度量值(sparseness...According to the Nyquist sampling theory which is the conventional one, it is required that the sampling frequency must be at least twice the highest frequency of signal to reconstruct the original signal accurately. Meanwhile, the compressive sensing theory proposed and being developed recently, can reconstruct the original ones properly and effectively from a small amount of samplings or measure...学位:工程硕士院系专业:信息科学与技术学院计算机科学系_计算机技术学号:X200622102

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