Abstract
White-noise correction is a technique used in speech coders using linear predictive coding (LPC). This technique generates an artificial noise-floor in order to avoid stability problems caused by numerical round-off errors. In this letter, we study the effect of white-noise correction on the roots of the LPC model. The results demonstrate in analytic form the relation between the noise floor level and the stability radius of the LPC model
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