Name
Title | ||
|---|---|---|
Optimal and sub-optimal algorithms for selecting the excitation in linear predictive coders |
Abstract | ||
|---|---|---|
A generalized coder that includes all types of excitation is presented. In this analysis-by-synthesis scheme, maximization formulae are the same regardless of the kind of excitation. The total excitation is expressed as a linear combination of excitation vectors. Given the number of excitation vectors or, equivalently, the bit rate of the coder, finding the vectors and their corresponding gains is a specific least-squares problem. The standard way this problem is usually solved is given, and three alternative mathematical approaches are proposed. These approaches are a Gram-Schmidt orthogonalization, a Choleski decomposition, a Householder transform. All these procedure have the same geometrical interpretation and lead to the same floating point simulation results |
Year | DOI | Venue |
|---|---|---|
1990 | 10.1109/ICASSP.1990.115755 | Albuquerque, NM |
Keywords | DocType | ISSN |
encoding,filtering and prediction theory,optimisation,speech analysis and processing,speech synthesis,choleski decomposition,gram-schmidt orthogonalization,householder transform,excitation vectors,least-squares problem,linear predictive coders,optimal algorithms,speech analysis,solid modeling,cholesky decomposition,analysis by synthesis,gram schmidt orthogonalization,signal analysis,speech,floating point,linear predictive coding,vectors,stochastic processes,filtering,least squares approximation | Conference | 1520-6149 |
Citations | PageRank | References |
9 | 1.04 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| P. Dymarski | 1 | 47 | 7.48 |
| Moreau, N. | 2 | 9 | 1.72 |
| Vigier, A. | 3 | 9 | 1.04 |