c13-6 (779569), страница 4
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Just do linear prediction until you are outside of tolerances, thenreinitialize (using M sequential stored residuals) and continue predicting.• In some applications, most notably speech synthesis, one cares only aboutthe spectral content of the reconstructed signal, not the relative phases.In this case, one need not store any starting values at all, but only theLP coefficients for each segment of the data. The output is reconstructedby driving these coefficients with initial conditions consisting of all zerosexcept for one nonzero spike. A speech synthesizer chip may have oforder 10 LP coefficients, which change perhaps 20 to 50 times per second.• Some people believe that it is interesting to analyze a signal by LPC, evenwhen the residuals xi are not small.
The xi ’s are then interpreted as theunderlying “input signal” which, when filtered through the all-poles filterdefined by the LP coefficients (see §13.7), produces the observed “outputsignal.” LPC reveals simultaneously, it is said, the nature of the filter andthe particular input that is driving it. We are skeptical of these applications;the literature, however, is full of extravagant claims..
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