Improved Generalized Sparsity Adaptive Matching Pursuit Algorithm Based on Compressive Sensing

Algorithm 2

Proposed algorithm.

	Input:
	Sensing matrix
	Observation vector
	Constant parameter
	Initial step size
	The number of atoms selected each time ;
	Tolerance used to exit loop
	Initialize parameter:
	{initialize signal approximation}
	{loop index}
	{initial sparsity estimate}
	{while loop flag}
	{empty preliminary index set}
	{empty candidate index set}
	{empty support index set}
	While (∼done)
(1)	Compute the projective set
(2)	Merge to update the candidate index set
(3)	Get the estimate signal value and residual error by least squares algorithm:
(4)	prune to obtain current support index set
(5)	update signal final estimate by least squares algorithm and compute residual error:
	residual error:
(6)	Check the iteration condition
	If
	quit iteration
	else if
	else
	end
	End
	Output:(s-sparse approximation of signal )