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本文运用AR模型的方法对大脑的一种重要暂态活动的脑电图——癫痫病人的脑电图进行了分析。用最大熵谱谱阵描述了癫痫发作前后,脑电图(EEG)能量分布随时间的变化过程,其结果比一般压缩功率谱阵满意。也尝试了利用模型极点中所谓“最活动极点”的轨迹来短期予报癫痫发作的方法,在有限病例的情况下,部分结果具有予报性。另外,讨论了在EEG分析中AR模型的阶数选择和数据长度的确定问题。
In this paper, the EEG model is used to analyze the EEG of epileptic patients, an important transient activity of the brain. The distribution of EEG energy distribution over time before and after epileptic seizure was described by maximum entropy spectral array, which was more satisfactory than that of general compressed power spectral array. Attempts have also been made to exploit the so-called “most active poles” trajectory in model poles to provide short-term reporting of seizures. In limited cases, some of the results are informative. In addition, we discuss the order selection and data length determination of AR model in EEG analysis.