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Table 4 Greedy algorithms

From: A unified approach to sparse signal processing

1. Let s ̂ = 0 n × 1 , r ( 0 ) =x, S ( 0 ) = and i=1.

2. Evaluate c j =〈r(i−1),a j 〉for j=1,,n where a j ’s are the columns of the mixing matrix A(atoms) and sort c j ’s as | c j 1 || c j n |.

3.  MP: Set S ( i ) = S ( i 1 ) j 1 .

 OMP: Set S ( i ) = S ( i 1 ) j 1 and A m × | S ( i ) | = a j j S ( i ) .

 CoSaMP: Set S ( i ) = S ( i 1 ) { j 1 ,, j 2 k } and A m × | S ( i ) | = a j j S ( i ) .

4.  MP: −−−

 OMP & CoSaMP: Find s ~ that A ( i ) · s ~ =x.

5.  MP & OMP: −−−

 CoSaMP: Sort the values of s ~ as | s ~ t 1 || s ~ t 2 | and redefine j 1 ,, j k as the indices of the columns in A that correspond to the columns t 1 ,, t k in A(i). Also set S ( i ) ={ j 1 ,, j k }.

6.  MP: Set ŝ j 1 = c j 1 .

 OMP & CoSaMP: Set ŝ j l = s ~ l for l=1,,k and ŝ l =0 where l S ( i ) .

7. Set r ( i ) =xA· s ̂ .

8. Stop if r ( i ) 2 is smaller than a desired threshold or when a maximum number of iterations is reached; otherwise, increase i and go to step 2.