Signal after denoising, respectively, using the ar model power spectrum estimation, wavelet packet decomposition coefficients and sub-band energy of the three feature extraction csp common space algorithm for eigenvalue extraction, the three eigenvalues ??substitution to the svm classifier in traini

For the noise of the signal, respectively, after using AR model of the power spectrum estimation, wavelet packet decomposition coefficients and with energy, CSP Common Space such a feature extraction algorithm 3 way feature Value Extraction, while the 3 characteristics of Generation values, respecti

After the denoising signal, uses the AR model the power spectrum to estimate separately, the small wave packet resolution ratio and the innertube energy, the CSP common space algorithm three characteristic extraction way carries on the characteristic value extraction, simultaneously substitutes thre

After the noise signal, respectively, using the power of AR model spectral estimation, coefficients and Wavelet packet Decomposition algorithm for subband energy, CSP common space feature extraction of three kinds of methods for extraction of characteristic values, while three characteristic values

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