By Topic

Asymptotic distribution of the errors in scalar and vector quantizers

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Lee, D.H. ; Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA ; Neuhoff, D.L.

High-rate (or asymptotic) quantization theory has found formulas for the average squared length (more generally, the qth moment of the length) of the error produced by various scalar and vector quantizers with many quantization points. In contrast, this paper finds an asymptotic formula for the probability density of the length of the error and, in certain special cases, for the probability density of the multidimensional error vector, itself. The latter can be used to analyze the distortion of two-stage vector quantization. The former permits one to learn about the point density and cell shapes of a quantizer from a histogram of quantization error lengths. Histograms of the error lengths in simulations agree well with the derived formulas. Also presented are a number of properties of the error density, including the relationship between the error density, the point density, and the cell shapes, the fact that its qth moment equals Bennett's integral (a formula for the average distortion of a scalar or vector quantizer), and the fact that for stationary sources, the marginals of the multidimensional error density of an optimal vector quantizer with large dimension are approximately i.i.d. Gaussian

Published in:

Information Theory, IEEE Transactions on  (Volume:42 ,  Issue: 2 )