| 摘要 |
Features are extracted from a sample input signal by performing first linear predictive analyses of different first orders p on the sample values and performing second linear predictive analyses of different second orders q on the residuals of the first analyses. An optimum first order &upbar& p is selected using information entropy values representing the information content of the residuals of the second linear predictive analyses. One or more optimum second orders &upbar& q are selected on the basis of changes in these information entropy values. The optimum first and second orders are output as features. Further linear predictive analyses can be carried out to obtain higher-order features. Useful features are obtained even for nonstationary input signals. |
