求和积码矢量量化器的联合码本设计

W. Chan, A. Gersho, S. Soong
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引用次数: 4

摘要

对于结构化矢量量化的广义积码(GPC)模型,多级积码(MSVQ)和树结构积码(VQ)是由原型综合函数x=f/sub 1/+…定义的求和积码(spc)族的成员。+f/s /,其中f/ i/, i=1,…,s为残差向量特征。作者描述了组成GPC的特征码本联合设计的算法范例。他们将范例专门用于SPCs的联合设计算法,并展示了模拟源的MSVQ的实验结果。与传统的“贪婪”设计相比,性能改进基本上是“免费的”,因为唯一的成本是设计复杂性的适度增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Joint codebook design for summation product-code vector quantizers
With respect to the generalized product code (GPC) model for structured vector quantization, multistage VQ (MSVQ) and tree-structured VQ are members of a family of summation product codes (SPCs), defined by the prototypical synthesis function x=f/sub 1/+...+f/sub s/, where f/sub i/, i=1, . . ., s are the residual vector features. The authors describe an algorithm paradigm for the joint design of the feature codebooks constituting a GPC. They specialize the paradigm to a joint design algorithm for the SPCs and exhibit experimental results for the MSVQ of simulated sources. The performance improvements over conventional 'greedy' design are essentially 'free' as the only cost is a moderate increase in design complexity.<>
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