Individual convergence rates in empirical vector quantizer design

  title={Individual convergence rates in empirical vector quantizer design},
  author={Andr{\'a}s Antos and L{\'a}szl{\'o} Gy{\"o}rfi and Andr{\'a}s Gy{\"o}rgy},
  journal={IEEE Transactions on Information Theory},
We consider the rate of convergence of the expected distortion redundancy of empirically optimal vector quantizers. Earlier results show that the mean-squared distortion of an empirically optimal quantizer designed from n independent and identically distributed (i.i.d.) source samples converges uniformly to the optimum at a rate of O(1//spl radic/n), and that this rate is sharp in the minimax sense. We prove that for any fixed distribution supported on a given finite set the convergence rate is… CONTINUE READING
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