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S. Voran, "Reducing Quantization Error by Matching Pseudoerror Statistics,"
Proceedings of the 12th IEEE Digital Signal Processing Workshop, Grand Teton
National Park, Wyoming, September 24-27 2006.
Abstract:
We investigate the use of an adaptive processor (a quantizer
pseudoinverse) and the statistics of the associated pseudoerror signal
to reduce quantization error in scalar quantizers when a small amount
of prior knowledge about the signal x is available. This approach
uses both the quantizer representation points and the thresholds at the
receiver. No increase in the transmitted data rate is required. We
discuss examples that use low-pass, high-pass, and band-pass signals
along with an adaptive processor that consists of a set of filters and
clippers. Matching a single pseudoerror statistic to a target value is
sufficient to attain modest reductions in quantization error in
situations with one degree of freedom. Adaptive processing based on
a pair of pseudoerror statistics allows for quantization noise reduction
in problems with two degrees of freedom.
Full Paper
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