| Full text | |
| Author(s): |
Ramirez, Miguel Arjona
[1]
Total Authors: 1
|
| Affiliation: | [1] Univ Sao Paulo, Escola Politecn, Dept Elect Syst Engn, PSI, BR-05508970 Sao Paulo - Brazil
Total Affiliations: 1
|
| Document type: | Journal article |
| Source: | IEEE SIGNAL PROCESSING LETTERS; v. 15, p. 99-102, 2008. |
| Web of Science Citations: | 1 |
| Abstract | |
Starting from the Durbin algorithm in polynomial space with an inner product defined by the signal autocorrelation matrix, an isometric transformation is defined that maps this vector space into another one where the Levinson algorithm is performed. Alternatively, for iterative algorithms such as discrete all-pole (DAP), an efficient implementation of a Gohberg-Semencul (GS) relation is developed for the inversion of the autocorrelation matrix which considers its centrosymmetry. In the solution of the autocorrelation equations, the Levinson algorithm is found to be less complex operationally than the procedures based on GS inversion for up to a minimum of five iterations at various linear prediction (LP) orders. (AU) | |