Linear Analog Coding of Correlated Multivariate Gaussian Sources
作者： I. Esnaola , A. M. Tulino , J. Garcia-Frias
DOI: 10.1109/TCOMM.2013.061013.110762
关键词:
摘要: The effect of prior knowledge when linear analog codes are used as joint source-channel for sources modeled multivariate Gaussian processes is analyzed. We use information theoretic tools to evaluate the achievable performance gain obtained by exploiting knowledge. In order assess validity in practical scenarios, where exact source statistics not known, we study having partial statistics. model mismatch an additive perturbation matrix between real covariance and postulated recovery process. this setting, obtain closed form expressions a deterministic using random theory characterize loss i.i.d. matrices.
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