摘要
通过分析比较非线性时间序列动力学分析过程中使用的各种算法,选择出适合脑电分析的算法。这些算法时空复杂度较高,计算耗时。我们对这些算法进行了串行优化和改进,使其时间复杂度有不同程度的降低,并提高了其准确度;再对其进行并行化,进一步提升了算法效率。最后整个计算过程运行时间缩短为优化前运行时间的1/50。在此基础上,我们提出了脑电非线性动力学快速分析系统的设计,并使用该系统分析了癫痫脑电数据,取得了良好的结果。
We chose several algorithms that are fit for analyzing EEG by comparing many algorithms used in the analysis of nonlinear time series. These algorithms are complex on both time and space, and they spend a lot of time computing. These algorithms were optimized and modified to reduce their complexity on time and to improve their precision. To improve the efficiency of these algorithms, we paralleled these algorithms. The whole computing process cost 1/50 of the time cost by the original algorithms finally. After that, an EEG＇s nonlinear dynamic fast analysis system was designed. At last, we used the EEG＇s nonlinear dynamic fast analysis system to analyze epileptic＇s EEG and have got good result.
出处
《生物医学工程研究》
2008年第3期154-157,162,共5页
Journal Of Biomedical Engineering Research
基金
国家自然科学基金资助项目(60434010)
关键词
脑电
非线性系统
关联维
优化及改进
并行化
：Electroencephalogrmn
Nonlinear system
Correlation dimension
Optimize and modify
Parallelled
