. Author manuscript; available in PMC: 2017 Aug 1.

Published in final edited form as: Signal Processing. 2016 Feb 6;125:274–289. doi: 10.1016/j.sigpro.2016.01.021

Algorithm 2.

NNS-SP

Input: Φ, Y, p, and S.

Output: X̂ and Λ̂_SS.

Initialization: Set R⁽⁰⁾ = Y and

{\hat{Λ}}_{S S}^{(0)} = \emptyset

Iteration: for j = 1, 2, … until stopping criteria are satisfied

1. Set Γ⁽^j⁾ to be the indices of the S largest μ_nn(ϕ_i, R⁽^j⁻¹⁾) values.

2. Set

{\hat{Λ}}_{S S}^{(j)} = {\hat{Λ}}_{S S}^{(j - 1)} \cup Γ^{(j)}

3. Update X̂⁽^j⁾ according to (11).

4. Redefine

{\hat{Λ}}_{S S}^{(j)}

as the indices of the S rows of X̂⁽^j⁾ with the largest Frobenius norms.

5. Update X̂⁽^j⁾ according to (11).

6. Update R⁽^j⁾ = Y − ΦX̂⁽^j⁾.