Greedy Algorithms promoting Group Sparsity V3: A=matrix_normalizer(B) - File Exchange

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A=matrix_normalizer(B)
BMP(A, y, group, err) Block Matching Pursuit
BOLS(A, y, group, err) Block Orthogonal Least Squares - selection of group based on highest
BOMP(A, y, group, err) Block Orthogonal Matching Pursuit - selection of group based on highest
GMP(A, y, group, err) Group Matching Pursuit
GOLS(A, y, group, err) Group Orthogonal Least Squares - selection of group based on highest
GOMP(A, y, group, err) Group orthogonal Matching Pursuit - selection of group based on highest
GenGroupSparseProblem(m, n, n... Initialize random number generator
ReGOMP(A, y, group, sparsity,... Regularized Group Orthogonal Matching Pursuit - Combining ideas from [1]
StGOMP(A, y, group, steps, er... Stagewise Group Orthogonal Matching Pursuit - Combining Ideas from [1]
[s, err_mse, iter_time]=block... block_gp: Block Gradient Pursuit algorithm (modification from [1])
[s, err_mse, iter_time]=block... group_nomp: Block Nearly Orthogonal Matching Pursuit algorithm
[s, err_mse, iter_time]=block... group_pcgp: Block Partial Conjugate Gradient Pursuit algorithm
[s, err_mse, iter_time]=group... group_gp: Group Gradient Pursuit algorithm (modification from [1])
[s, err_mse, iter_time]=group... group_nomp: Group Nearly Orthogonal Matching Pursuit algorithm
[s, err_mse, iter_time]=group... group_pcgp: Group Partial Conjugate Gradient Pursuit algorithm
fdrthresh(z,q)
demo.m
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from Greedy Algorithms promoting Group Sparsity V3 by Angshul Majumdar
Approximate Greedy Solutions to the problem min||x(k)||_2,0 such that Ax = b

A=matrix_normalizer(B)
function A=matrix_normalizer(B) [m n] = size(B); for i = 1:n A(:,i) = B(:,i)/norm(B(:,i)); end