EEG signal analysis using FB expansion and second-order linear TVAR process

详细信息    查看全文

• 作者：Ram Bilas Pachori ; Pradip Sircar
• 关键词：Parametric modeling ; Linear time-varying autoregressive process ; Fourier– ; Bessel series expansion ; Electroencephalogram signal
• 刊名：Signal Processing
• 出版年：2008
• 出版时间：February 2008
• 年：2008
• 卷：88
• 期：2
• 页码：415-420
• 全文大小：160 K

文摘

In this paper, we propose a second-order linear time-varying autoregressive (TVAR) process for parametric representation of the electroencephalogram (EEG) signals. The coefficients of the Fourier–Bessel (FB) series expansion have been used to constitute a feature vector for segmentation of the EEG signal. Our approach is novel in the sense that by selecting an appropriate data length, we find a simple model for parametric representation of the EEG signals. The complete method for estimation of model parameters is presented in this work.