Companding and random quantization in several dimensions

Authors:
J. Bucklew
Affiliations:
-
Venue:
IEEE Transactions on Information Theory
Year:
2006

Citing 0
Cited 3

Optimal companding vector quantization for circularly symmetric sources

Information Sciences: an International Journal
Learning a multi-dimensional companding function for lossy source coding

Neural Networks
Geometric piecewise uniform lattice vector quantization of the memoryless Gaussian source

Information Sciences: an International Journal

Quantified Score

Hi-index	754.84

Visualization

Abstract

The problem of implementing multidimensional quantizers is discussed. A general equation is derived that can be used to evaluate the performance of multidimensional compandors. It is demonstrated that the optimal compandor must be conformal almost everywhere. An example is given to show that asymptotically optimal performance could be obtained through nonconformal companding schemes. Random quantizers are discussed and two techniques are evaluated for reducing memory and computation time in the implementation of such devices.