Distributed Compression of Correlated Signals Using Random Projections

摘要: Recent developments in compressed sensing have shown that if a signal can be some basis, then it reconstructed such basis from certain number of random projections. Distributed sensing, where several correlated signals are distributed manner, has also been proposed the literature. By allowing additional distortion, successful recovery achieved even projections corrupted by noise. We extend this result showing addition to sparsity, is possible exploit prior knowledge existing correlation between interest significantly improve reconstruction performance. This done fashion resembling coding digital sources.