Optimization-quantization for least squares estimates and its application for lossless audio compression

In this paper we study the problem of optimally quantizing the least square estimates and we introduce a method where the quantized estimate vector is obtained by a sequence of interleaved optimization-quantization scalar stages. We show how the general approach can be reduced to a simple and efficient algorithm when connecting it to the LDL^T solver for general LS problems. The application to quantization of the linear prediction coefficients for audio lossless coding reveals the high performance of the approach, leading to topmost performance in the class of frame based audio coders, surpassing significantly the performance of the current MPEG4-ALS standard.