Enhancing Temporal Classification of AAR Parameters in EEG single-trial analysis for Brain-Computer Interfacing
作者： G.S. Dharwarkar , O. Basir
DOI: 10.1109/IEMBS.2005.1615692
关键词:
摘要: Adaptive autoregressive (AAR) coefficients provide dynamic spectral information in EEG single-trial analysis. In this paper we propose a temporal evidence accumulation framework to enhance classification of AAR features. The results for single subject, using 280 trials, indicate distinct improvements over conventional method classification. We illustrate how the is applicable features, as well wavelet features reported Lemm et al., (2004). These findings put two time-frequency on equal footing comparison context
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