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Cascaded RLS–LMS Prediction in MPEG-4 Lossless Audio Coding

机译:MPEG-4无损音频编码中的级联RLS–LMS预测

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This paper describes the cascaded recursive least square–least mean square (RLS–LMS) prediction, which is part of the recently published MPEG-4 Audio Lossless Coding international standard. The predictor consists of cascaded stages of simple linear predictors, with the prediction error at the output of one stage passed to the next stage as the input signal. A linear combiner adds up the intermediate estimates at the output of each prediction stage to give a final estimate of the RLS–LMS predictor. In the RLS–LMS predictor, the first prediction stage is a simple first-order predictor with a fixed coefficient value 1. The second prediction stage uses the recursive least square algorithm to adaptively update the predictor coefficients. The subsequent prediction stages use the normalized least mean square algorithm to update the predictor coefficients. The coefficients of the linear combiner are then updated using the sign–sign least mean square algorithm. For stereo audio signals, the RLS–LMS predictor uses both intrachannel prediction and interchannel prediction, which results in a 3% improvement in compression ratio over using only the intrachannel prediction. Through extensive tests, the MPEG-4 Audio Lossless coder using the RLS–LMS predictor has demonstrated a compression ratio that is on par with the best lossless audio coders in the field. In this paper, the structure of the RLS–LMS predictor is described in detail, and the optimal predictor configuration is studied through various experiments.
机译:本文介绍了级联递归最小二乘最小均方(RLS-LMS)预测,它是最近发布的MPEG-4音频无损编码国际标准的一部分。预测器由简单线性预测器的级联组成,一级的输出端的预测误差作为输入信号传递到下一级。线性组合器将每个预测阶段输出的中间估计值相加,得出RLS-LMS预测值的最终估计值。在RLS–LMS预测器中,第一预测阶段是具有固定系数值1的简单一阶预测器。第二预测阶段使用递归最小二乘算法自适应地更新预测器系数。随后的预测阶段使用归一化的最小均方算法来更新预测系数。然后使用正负号最小均方算法更新线性组合器的系数。对于立体声音频信号,RLS–LMS预测器同时使用通道内预测和通道间预测,与仅使用通道内预测相比,压缩率提高了3%。通过广泛的测试,使用RLS–LMS预测器的MPEG-4音频无损编码器已经证明了其压缩率与业内最佳的无损音频编码器相当。在本文中,详细描述了RLS–LMS预测器的结构,并通过各种实验研究了最佳预测器配置。

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