Matrix analysis and applied linear algebra
Matrix analysis and applied linear algebra
Exploiting Prior Knowledge in The Recovery of Signals from Noisy Random Projections
DCC '07 Proceedings of the 2007 Data Compression Conference
Distributed Compression of Correlated Signals Using Random Projections
DCC '08 Proceedings of the Data Compression Conference
Decoding by linear programming
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Signal Reconstruction From Noisy Random Projections
IEEE Transactions on Information Theory
Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
IEEE Transactions on Information Theory
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We study the performance of distributed analog linear coding of correlated multivariate Gaussian sources over the multiple access channel. Assuming the correlation structure is known both at the encoder and the decoder, optimal linear encoding and decoding is introduced. A general performance analysis is presented for both random and optimal linear encoders and compared to a lower bound on the achievable theoretical limit. Simulation results show the agreement between the theoretical analysis and the practical implementation.