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Paper A Theory of Nonsubtractive Dither

From Robert A. Wannamaker’s Paper

1. Introduction

A. The Classical Model of Quantization

For Mid-tread quantization

\[Q(w) = \Delta \lfloor \frac{w}{\Delta} + \frac{1}{2} \rfloor\]

where $\lfloor . \rfloor$ is floor function, e.g.,

\[\begin{align} \lfloor 0.5 \rfloor &= 0\\ \lfloor 1 \rfloor &= 1\\ \lfloor 1.5 \rfloor &= 1 \end{align}\]

B. Dither: Subtractive versus Nonsubtractive

For SD (subtractively diththered), total error is

\[\varepsilon = q(x+\nu)\]

For nonsubstractively dithered system

\[\varepsilon = q(x+\nu) + \nu\]

Nonsubtractively dither Nonsubtractively dither

define total error

\[\varepsilon \overset{\triangle}{=} output - input = D_{OUT} - D_{ACC}\]

It has been shown by Schuchman that

Nonsubtractive Dither Theory

A. Total Error PDF’s

The input to the quantizer is \(w=x+\nu\), which is the sum of the system input and the statistically independent dither process. This sum has a cpdf \(p_{w|x}(w,x) = p_{\nu}(w-x)\). If the quantizer outputs \(k\Delta\), the total error is \(k\Delta - x\)

\[p_{\varepsilon|x}(\varepsilon,x) = \sum_{k=-\infty}^{\infty} \delta(\varepsilon + x - k\Delta) \int_{-\frac{\Delta}{2} + k\Delta}^{\frac{\Delta}{2} + k\Delta} p_{\nu}(w-x)dw\]

given \(\varepsilon\) and \(x\), there is at most one \(k\) such that \(\delta(\varepsilon + x - k \Delta)\) is not zero. Writing the integral in the last equation as a convolution (which is denoted by \(*\)) of \(p_{\nu}\) with a rectangular window function \(\Delta \Pi_{\Delta}\) reduces it to

\[p_{\varepsilon|x}(\varepsilon,x) = [\Delta \Pi_{\Delta} * p_{\nu}](\varepsilon)W_{\Delta}(\varepsilon + x)\]

where

\[W_{\Gamma}(\varepsilon) \overset{\triangle}{=} \sum_{k=-\infty}^{\infty} \delta(\varepsilon - k\Gamma)\]

Thus, the pdf of \(\varepsilon\) is given by (since \(W_{\Delta}(\varepsilon)\) is even function)

\[\begin{align} p_{\varepsilon}(\varepsilon) &= \int_{-\infty}^{\infty} p_{\varepsilon|x}(\varepsilon,x) p_x(x)dx\\ &= [\Delta\Pi_{\Delta} * p_{\nu}](\varepsilon) [W_{\Delta} * p_x](-\varepsilon) \end{align}\]

Theorem:

\(E[\varepsilon^m]\) is independent of the distribution of the input \(D_{ACC}\) if and only if

\[\frac{\partial^m}{\partial u^m}[\mathrm{sinc}(u) \cdot \mathcal{F}[p_{\nu}](u)] \bigg|_{u=k} = 0\]

for all integer \(k\) with exception of 0. Where

\[\begin{align*} \mathrm{sinc}(u) &= \frac{\sin(\pi u)}{\pi u}\\ \mathcal{F}[p_{\nu}](u) &= \int_{-\infty}^{\infty} p_{\nu}(x) e^{-j2\pi u x} dx \end{align*}\]
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