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. 2019 Apr 10;19(7):1718. doi: 10.3390/s19071718

Algorithm 1 FBS algorithm for

ℓ_{1}

-norm penalized least squares problem

Input:

x^{(0)}, A, A^{T}, λ

Output:

x^{(i + 1)}

1:
Set $ρ = m a x e i g (∥ A^{T} A ∥)$
2:
Set $μ : 0 < μ < 1 / ρ$
3:
Number of iteration: $N_{i t e r}$
4:
for $i = 0 t o N_{i t e r}$ do
5:
$w^{(i)} = x^{(i)} - μ A^{T} (A x^{(i)} - d_{w})$
6:
$x^{(i + 1)} = s o f t (w^{(i)}, μ λ)$
7:
end for
8:
return $x^{(i + 1)}$