Design of entropy-constrained quantizers based on coset codes

Cheng-Chieh Lee, N. Farvardin
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Abstract

Asymptotic vector quantization (VQ) theory indicates that at high rates, the optimal VQ uniformly places its reproduction vectors in the high dimensional space in a manner that each of the quantization cells is made as spherical as possible. As compared with scalar quantizers whose quantization cells are cubic, VQ exploits the space-filling efficiency of its constituent convex polytope and hence achieves the so-called granular gain.<>
基于协集码的熵约束量化器设计
渐近矢量量化(VQ)理论表明,在高速率下,最优的VQ均匀地将其复制向量放置在高维空间中,使每个量化单元尽可能呈球形。与量化单元为立方的标量量化器相比,VQ利用了其组成凸多面体的空间填充效率,从而实现了所谓的颗粒增益。
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