Verification-based message-passing algorithms in compressed sensing

<p>Verification-based message-passing <a href="/facts/Algorithms/fnl5NmRt">algorithms</a> (VB-MPAs) in <a href="/facts/Compressed_sensing/aR5DQm3n">compressed sensing</a> (CS), a branch of <a href="/facts/Digital_signal_processing/PEG7azr8">digital signal processing</a> that deals with measuring <a href="/facts/Compressed_sensing/aR5DQm3n">sparse signals</a>, are some methods to efficiently solve the recovery problem in compressed sensing. One of the main goal in compressed sensing is the recovery process. Generally speaking, recovery process in compressed sensing is a method by which the original signal is estimated using the knowledge of the compressed signal and the measurement matrix. Mathematically, the recovery process in Compressed Sensing is finding the sparsest possible solution of an under-determined <a href="/facts/System_of_linear_equations/fk9CFdgp">system of linear equations</a>. Based on the nature of the measurement matrix one can employ different reconstruction methods. If the measurement matrix is also sparse, one efficient way is to use Message Passing Algorithms for signal recovery. Although there are message passing approaches that deals with dense matrices, the nature of those algorithms are to some extent different from the algorithms working on sparse matrices.
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Verification-based message-passing algorithms in compressed sensing open-in-new

Verification-based message-passing algorithms in compressed sensing