【作者】 张新军；

【导师】 沈民奋；

【作者基本信息】 汕头大学 ， 信号与信息处理， 2003， 硕士

【摘要】 近年来，信号处理的理论与方法获得了迅速发展。事实证明，信号处理是推动众学科发展的一个重要基石。独立分量分析技术(ICA)是信号处理领域发展较晚的一种理论与方法，已迅速成为该领域内重要的组成部分，且其发展逐渐趋向成熟化与系统化。 本文系统地介绍了独立分量分析的理论与方法，同时将其应用到有价值的实际诱发脑电信号和数字图像信号分离中。 本文内容包括：脑科学及脑电信号分析方法现状，独立分量分析理论，诱发电位提取技术研究进展，数字图像水印分类与处理算法以及独立分量分析在脑电(EEG/VEP)及数字图像水印处理中的试验，最后总结了本论文的工作及需要解决的一些问题与下一步的发展方向。 独立分量分析技术可以很好地分离出EEG数据中的肌电与眼动等干扰；实现了VEP的增强与提取；很好地分离数字图像信号中的水印与密钥，即使在很强的干扰情况下，仍具有很好的性能指标。这些结果充分展示出ICA技术良好的信号处理能力和应用价值。更多还原

【Abstract】 Recently, theories and methods of signal processing are obtained to develope quickly. In fact, signal processing is a important foundation stone for all kinds of subjects’ developing. Independent component analysis (ICA) technology developing is a later theory or method in fields of signal processing, but it was important that rapidly become a part of constitution of signal processing fields, and its developing tends gradually to maturity and systematization.This paper introduced theory and method of independent component analysis by the numbers. At the same time , it was applied to process Evoked Electroencephalography (EEG) signal which it has very important value, and to process digital image signal.This paper’s contents include: brain science and analytical actuality of EEG signal, theory of ICA, research headway of evoked potential (EP) extraction technique, classes and processing algorithms of digital image watermarking, and ICA technology’s application (in EEG/VEP and digital image watermarking processing), finally, summarized the work of this paper and some problems on the ICA technique which to be solved were presented and the direction of the development pointed out.The ICA technique separated successfully electromyographic (EMG) and electro-Oculographic (EOG) artifacts from EEG data ; accomplished VEP strengthening and extraction; separated watermarking and key from mixing digital image signals, even though under strong noise, the results still have very good performance index. All above showed nicer signal processing ability and factual value of ICA technique.更多还原