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Most biomedical signals are low frequency signals and usually submerged by stronger noises. It is not easy to extract their features using the normal filter methods. Independent component analysis (ICA) in signal processing has the ability of recovering independent source signals after they are linearly mixed by an unknown medium. In this article we first discuss the ICA model and the principle of...
The brain evoked potentials (BEP) are related directly to series of diseases and physical states. It is helpful to prevent and diagnose the brain diseases by recognizing the evoked potential. In this paper, we use the traditional average method and the wavelet transformation technology to wipe off the noise and extract the feature for the instantaneous visual evoked potential (VEP) at first. Then...
In single trial source separation problem of VEP signals, the selection of legitimate Principal Components (PCs) is an important phenomenon. The Spectral Power Ratio (SPR) method developed by us earlier for PCA has proven to be capable of selecting only the required PCs in a sophisticated manner. Our continuous enhancement has lead to the current development of the proposed method, Sandwich SPR (SSPR)...
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