摘 要
当今，我们正处在一个高速发展的信息时代，为了有效地利用现代通讯业务和信息处理中的宝贵资源，需要对大量的数据信息进行处理，因此信号数据压缩技术和解压缩技术成了多媒体技术的关键技术之一。
本文简要研究了近年来小波分析的发展及其在信号处理方面的应用情况，然后引入了小波变换的一些基本理论，在此基础上提出了小波包变换。小波包变换对信号进行压缩和消噪的原理和小波变换的基本相同，不同的是小波包变换属于线性时频分析法，因而具有良好的时频定位特性以及对信号的自适应能力，能够对各种时变信号进行有效的分解。最后本文系统地描述了目前常用的小波包对信号消噪和压缩的方法，利用Matlab的小波工具箱中的函数进行了一些实验，通过实验结果比较看出小波包处理信号的效果好于小波变换。
关键词：小波变换; 小波包变换; 信号压缩; 信号消噪
Abstract
Today, we are engaged in a high-speed development of the information age. In order to effectively use modern communication and information processing operations of valuable resources，we need deal with a large amount of date and information. Therefore, the signal compression and decompression technology has become one of the key multimedia technologies.
This paper briefly studied the development of the wavelet analysis and its application in signal processing in recent years, and then introduced some basic theory in wavelet transform. On this basis, we recommend the wavelet packets transform. The basic method used wavelet packets transform in signal de-noising and compression is closed to the method used by wavelet transform. The differences are that wavelet packets transform have good time-frequency orienting feature and adaptive faculty in signals, so it is more effective in processing signals. At last we use Wavelet Toolbox to carry out some experiments. Comparing from the experiment, we proved the theory above.
Keywords : wavelet transform ; wavelet packets transform ; signal de-noising; signal compression
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