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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
