Abstract
The letter deals with the development of a simplified fast least-squares algorithm which is free of roundoff error accumulation. The simplified algorithm requires 9N MADPR (multiplications and divisions per recursion) rather than 10N MADPR as in the fast least squares or fast Kalman (FLS) case where N is the order of predictor. The superiority of SFLS over FLS and LMS approaches is illustrated by prediction gain performance curves for various speech signals.
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