| Summary: | 碩士 === 國立交通大學 === 電機與控制工程系 === 91 === Abstract
This thesis aims at two aspects: (1) design of a computerized interpretation system, adaptive-network-based fuzzy inference system (abbreviated as ANFIS), to classify the spectral features of EEG signals, and (2) application of the ANFIS system to the EEG signals recorded from both the experimental (meditators) and control (non-meditators) groups. The results of interpretation are demonstrated by means of running gray-level chart and statistical bar chart.
Strategies of designing the ANFIS include: applying wavelet decomposition to the EEG to quantify its spectral features, partition the spectral feature space to obtain the training data set, training the ANFIS based on pre-specified criteria, and finally testing its performance.
The designed ANFIS interpretation system will be used to analyze the spectral contents of the EEG in either meditation or relaxation. Perceivable differences between these two groups are observed from the results.
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