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arxiv: 1403.4311 · v1 · pith:RWNKC4NJnew · submitted 2014-03-18 · 🧮 math.NA · cs.IT· math.IT

The lower bound of the PCM quantization error in high dimension

classification 🧮 math.NA cs.ITmath.IT
keywords boundquantizationconjectureerrorframenotetightunit-norm
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In this note, we investigate the performance of the PCM scheme with linear quantization rule for quantizing unit-norm tight frame expansions for ${\mathbb R}^d$ without the White Noise Hypothesis. In \cite{WX}, Wang and Xu showed that for asymptotically equidistributed unit-norm tight frame the PCM quantization error has an upper bound ${\mathcal O}(\delta^{(d+1)/2})$ and they conjecture the upper bound is sharp. In this note, we confirm the conjecture with employing the asymptotic estimate of the Bessel functions.

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