A COMPUTER SIMULATION STUDY OF MUSIC ALGORITHM FOR EEG INVERSE PROBLEM

By using computer simulation, effectiveness of multiple signal classification (MUSIC) was evaluated. The head model used was the concentric 3 spheres conductor model. The EEG time course was reconstructed by the Total Least Squares (TLS). Two new parameters were proposed: Normalized Blurring Index (NBI) was used to indicate the spatial blurring level and Singular Value Ratio (SVR) was used to show the effectiveness of the signal noise subspace decomposition in the MUSIC algorithm. The general Relative Error (RE) and Correlation Coefficient (CC) were used to express the temporal reconstruction precision. It was simulated by using the different level of Gaussian white noise and the different correlation sources that the spatial blurring seriousness, the temporal reconstruction precision and the ability to decompose the signal and the noise subspace of the MUSIC algorithm. The results showed that the MUSIC algorithm was robust to the Gaussian white noise and sensitive to the sources correlation.