An efficient joint source-channel coding for a D-dimensional array
| dc.creator | Kanter, Ido | |
| dc.creator | Kfir, Haggai | |
| dc.creator | Keren, Shahar | |
| dc.date | 2003-08-15 | |
| dc.date.accessioned | 2026-07-07T02:52:56Z | |
| dc.date.available | 2026-07-07T02:52:56Z | |
| dc.description | An efficient joint source-channel (S/C) decoder based on the side information of the source and on the MN-Gallager Code over Galois fields, $q$, is presented. The dynamical posterior probabilities are derived either from the statistical mechanical approach for calculation of the entropy for the correlated sequences, or by the Markovian joint S/C algorithm. The Markovian joint S/C decoder has many advantages over the statistical mechanical approach, among them: (a) there is no need for the construction and the diagonalization of a $q \times q$ matrix and for a solution to saddle point equations in $q$ dimensions; (b) a generalization to a joint S/C coding of an array of two-dimensional bits (or higher dimensions) is achievable; (c) using parametric estimation, an efficient joint S/C decoder with the lack of side information is discussed. Besides the variant joint S/C decoders presented, we also show that the available sets of autocorrelations consist of a convex volume, and its structure can be found using the Simplex algorithm. | |
| dc.description | 19 pages and 12 figures | |
| dc.identifier | https://arxiv.org/abs/cond-mat/0308308 | |
| dc.identifier | http://arxiv.org/abs/cond-mat/0308308 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/22027 | |
| dc.subject | Statistical Mechanics | |
| dc.subject | Disordered Systems and Neural Networks | |
| dc.title | An efficient joint source-channel coding for a D-dimensional array | |
| dc.type | text |