Abstract

In this study, a robust classification method for emotional speech single-trial event-related potential (ERP) signal was developed. The classification method based on compression sensing (CS) theory. First, we use CS theory to reduce the dimensionality of the ERP signal. Second, the ERP signal was reconstructed by using K-SVD method to construct the over-complete redundant dictionary. Finally, the ERP signal was classified by calculating the residuals between the reconstructed samples and the test samples. The experimental results show that the proposed algorithm can effectively classify the noisy ERP signal and avoid the feature extraction process in the signal recognition.

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