A brief talk on compression perception (27): Sparse Adaptive matching tracking for compression-aware reconstruction algorithms (SAMP)

A brief talk on compression perception (27): Sparse Adaptive matching tracking for compression-aware reconstruction algorithms (SAMP)

Main content: Samp algorithm flow samp matlab Realization One-dimensional signal experiment and results experiment and results of the probability relationship between sparsity K and reconstruction Success first, Samp algorithm flow

As mentioned above, most of the OMP and its pre-modification algorithms need to know the sparsity of the signal k, and in practice this is generally unknown, based on this background, sparse adaptive matching tracking (sparsity Adaptive MP) was proposed. Samp does not need to know the sparsity K, in the iterative cycle, according to the new residuals and the old residual difference to determine the number of selected atoms.

Samp Algorithm Flow:

Second, the SAMP of MATLAB Implementation (CS_SAMP.M)

experiment and result of three or one-D signal

experiment and results of the relationship between sparse number k and the probability of reconstruction success

Vi. Articles of reference

http://blog.csdn.net/jbb0523/article/details/45675735