Name
Abstract | ||
|---|---|---|
The authors present a unified formulation and study of vector quantizer design methods that couple stochastic relaxation (SR) techniques with the generalized Lloyd algorithm. Two new SR techniques are investigated and compared: simulated annealing (SA) and a reduced-complexity approach that modifies the traditional acceptance criterion for simulated annealing to an unconditional acceptance of perturbations. It is shown that four existing techniques all fit into a general methodology for vector quantizer design aimed at finding a globally optimal solution. Comparisons of the algorithms' performances when quantizing Gauss-Markov processes, speech, and image sources are given. The SA method is guaranteed to perform in a globally optimal manner, and the SR technique gives empirical results equivalent to those of SA. Both techniques result in significantly better performance than that obtained with the generalized Lloyd algorithm |
Year | DOI | Venue |
|---|---|---|
1992 | 10.1109/78.124941 | Signal Processing, IEEE Transactions |
Keywords | Field | DocType |
data compression,encoding,picture processing,simulated annealing,speech analysis and processing,stochastic processes,Gauss-Markov processes,generalized Lloyd algorithm,globally optimal solution,image sources,reduced-complexity approach,simulated annealing,source coding,speech,stochastic relaxation,unconditional acceptance of perturbations,vector quantizer design | Simulated annealing,Speech processing,Mathematical optimization,Algorithm design,Computer science,Stochastic process,Vector quantization,Gaussian process,Quantization (signal processing),Data compression | Journal |
Volume | Issue | ISSN |
40 | 2 | 1053-587X |
Citations | PageRank | References |
63 | 14.64 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| K. Zeger | 1 | 1759 | 178.06 |
| J Vaisey | 2 | 91 | 17.04 |
| Allen Gersho | 3 | 2031 | 624.48 |