Lossless compression of digital audio using cascaded RLS-LMS prediction

R. Yu, C. Ko
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引用次数: 28

Abstract

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.
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使用级联RLS-LMS预测的数字音频无损压缩
提出了一种用于无损音频编码的级联RLS-LMS预测器。在该预测器中,采用高阶LMS预测器对音频信号的大量音调和谐波成分进行建模,以获得最佳的预测增益性能。为了解决彩色输入时LMS算法收敛缓慢的问题,在LMS预测器之前级联了一个低阶RLS预测器,以消除音频信号的频谱倾斜。这种级联的RLS-LMS结构有效地缓解了LMS算法收敛缓慢的问题,与传统的LMS预测器相比,提供了更好的预测增益性能,从而获得了更好的整体压缩性能。
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