# Quantize

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Related to quantizers: Quantization error, Quantization noise

## Quantize

To convert an asset or liability into a currency other than the regular trading currency.

## Quantize

To express or convert an asset or liability as a quantity of a currency other than the one in which it usually trades. For example, Americans trading stocks on the IPE in London must report their assets in dollars for United States tax purposes. See also: Foreign exchange.
References in periodicals archive ?
Furthermore, analysis and determination of support region for quasilogarithmic quantizers and the same source were presented in .
The superscript u stands for user and may refer to either Alice, in which case the quantizer is [Q.sup.A] (*) , or to Bob, for which the quantizer is [Q.sup.B] (*) .
The system is operating on frame-by-frame basis, where the quantizer is adapted to the short-term estimate of the frame variance.
Section 2 demonstrates the problem discussed and the CHO network; distributed protocol and logarithmic quantizer are illustrated there in detail.
Q(s) is transfer function of ideal quantizer and [Q.sub.e](s) is error characteristics of known saw-tooth shape with zero mean and peak-to-peak value of one quantization step q.
Hemami, "Sequential design of multiple description scalar quantizers," in Proc.
The G.711 standard (G.711 quantizer) defines fixed length coding that provides high quality of reconstructed signal for fixed bit rates .
The same bit allocation is utilized in all implemented modifications of the BTC algorithm, so that, for the given fixed bit rates of the three abovementioned quantizers, the total bit rate depends on the frame size, which is the only variable left in Eq.
for l=1: L [Q.sup.l] = {[c.sup.1.sub.l]} // initialization by using [C.sup.2.sub.1] [M.sup.l] = mean([Q.sup.l]) // [M.sup.l] is the centroid of quantizer [Q.sup.l] for k=2:K D(i,j) = d{[M.sup.i], // compute the initial distance [c.sup.k.sub.j]) idx = compute indicator(D) // idx(j), an indicator computed as Algorithm 3, for j=1:L [Q.sup.idx(j)] = [Q.sup.idx(j)] // update quantizers [union] [c.sup.k.sub.j] [M.sup.idx(j)] = // update quantizer centroids mean([Q.sup.idx(j)]) Algorithm 3 Computing idx from distance matrix D for l = 1: L idx(l) = l //initialize indicator for i = 1:L-1 for j = i +1:L if D(idx(i), i) + D(idx(j), j) < D(idx(j), i) + D(idx(i), j) swap(idx(i), idx(j)) // swap indicator 4.
where N is the average number of quantization levels of quantizers [Q.sub.1] and [Q.sub.2], whereas f is compression factor.
For each of the k range two quantizers are designed: 1) quantizer which provides the smallest quantization error or minimum distortion if the assumed distribution of the amplitude of the signal source is described by Laplacian function and 2) quantizer which provides the smallest quantization error when assumed distribution of sources is described by Gaussian function.
On our disposal are k quantizers designed for variances [[??].sup.2.sub.p], p = 1, ..., k, that have been log-uniformly distributed in the dynamic range of variances B = 20 log ([[sigma].sub.max] / [[sigma].sub.min])
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