Lossless compression of digital audio using cascaded RLS-LMS prediction

摘要

This paper proposes a cascaded RLS-LMS predictor for lossless audio coding. In this proposed predictor, a high-order LMS predictor is employed to model the ample tonal and harmonic components of the audio signal for optimal prediction gain performance. To solve the slow convergence problem of the LMS algorithm with colored inputs, a low-order RLS predictor is cascaded prior to the LMS predictor to remove the spectral tilt of the audio signal. This cascaded RLS-LMS structure effectively mitigates the slow convergence problem of the LMS algorithm and provides superior prediction gain performance compared with the conventional LMS predictor, resulting in a better overall compression performance.