Multidimensional matching pursuit algorithm
You can install the latest version through pip
pip install git+https://github.com/WiSeCom-Lab/MOMP-core
You will first have to define the algorithm through three pieces: the algorithm structure, the projection step and the stop condition
algorithm = core(projection, stop)
Once the algorithm is defined you can simply pass the data you want to decompose to get the sparse decomposition index and values
I, alpha = algorithm(data)
Found in MOMP.mp, the core indicating the workflow of the algorithm.
It can either be MP for plain matching pursuit or OMP for orthogonal matching pursuit.
Found in MOMP.proj, the projection step is the main innovation in MOMP, this one can be
OMP_proj(A, X) is the classic OMP projection step for the measurement matrix A and the dictionary X
MOMP_proj(A, X) is the MOMP projection step for the measurement matrix A and the dictionaries collection X
Found in MOMP.stop, the stop criteria determines when to stop the algorithm run.
General(maxIter) determines the maximum number of algorithm iterations