Improved Stochastic Gradient Matching Pursuit Algorithm Based on the Soft-Thresholds Selection

Algorithm 1

StoGradMP algorithm.

	Input:
	Sparsity level
	Sensing matrix
	Observation vector
	Block size
	Tolerance used to exit loop
	Maximum number of iterations
	Initialization parameter:
	{initialize signal approximation}
	{loop index}
	{while loop flag}
	{empty preliminary index set}
	{empty candidate index set }
	{empty support index set}
	{number of block}
	While (∼done)
	(1) Randomize
	(2) Computation of gradient
	(3) Identify the large components
	(4) Merge to update candidate index set
	(5) Signal estimation by the least square method
	(6) Prune to obtain current support index set
	(7) Update
	(8) Check the iteration condition
	If
	done = 1 quit iteration
	end
	end
	Output: (s-sparse approximation of signal )