Name
Abstract | ||
|---|---|---|
The effect of prior knowledge when linear analog codes are used as joint source-channel codes for sources modeled as multivariate Gaussian processes is analyzed. We use information theoretic tools to evaluate the achievable performance gain obtained by exploiting prior knowledge. In order to assess the validity of linear codes in practical scenarios, where exact source statistics are not known, we study the effect of having partial knowledge of the statistics. We model the mismatch of the statistics as an additive perturbation matrix between the real covariance matrix and the postulated covariance matrix in the recovery process. In this setting, we obtain closed form expressions for a deterministic perturbation matrix and using random matrix theory tools we characterize the performance loss for i.i.d. random matrices. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/TCOMM.2013.061013.110762 | IEEE Transactions on Communications |
Keywords | Field | DocType |
Gaussian processes,combined source-channel coding,covariance matrices,linear codes,additive perturbation matrix,closed form expression,correlated multivariate Gaussian source,covariance matrix,deterministic perturbation matrix,information theoretic tool,joint source-channel code,linear analog coding,random matrix theory tool,Gaussian processes,Linear codes,mismatch,prior knowledge | Applied mathematics,Generator matrix,Estimation of covariance matrices,Control theory,Theoretical computer science,Multivariate normal distribution,Multivariate random variable,Gaussian process,Covariance matrix,Mathematics,Scatter matrix,Covariance | Journal |
Volume | Issue | ISSN |
61 | 8 | 0090-6778 |
Citations | PageRank | References |
2 | 0.40 | 16 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Inaki Esnaola | 1 | 87 | 10.43 |
| A. M. Tulino | 2 | 1362 | 101.89 |
| Javier Garcia-Frias | 3 | 716 | 69.63 |