Sub-Linear Time Support Recovery for Compressed Sensing Using Sparse-Graph Codes
Sub-Linear Time Support Recovery for Compressed Sensing Using Sparse-Graph Codes is a scholarly work, published in 2019 in ''IEEE Transactions on Information Theory''. The main subjects of the publication include low-density parity-check code, matrix, sparse matrix, decoding method, 5G, theoretical computer science, signal reconstruction, Basis pursuit, computer science, signal processing, compressed sensing, mathematics, graph dimension, and algorithm. The authors formally connect this general recovery problem with sparsegraph decoding in packet communication systems and analyze the authors' framework in terms of the measurement cost, computational complexity, and recovery performance.