Table 2 Pseudocode of the QR-CS reconstruction algorithm.
From: Reconstruction of Complex Network based on the Noise via QR Decomposition and Compressed Sensing
Algorithm 1 QR-CS reconstruction algorithm |
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Require:\(Y\in {R}^{N\times P}\), \(X\in {R}^{N\times P}\) and \(U\in {R}^{M\times P}\) |
Ensure: \(A\in {R}^{N\times N}\) and \(B\in {R}^{N\times M}\) |
1: input \(U\in {R}^{M\times P}\), set \({\parallel B\parallel }_{0}=k\) |
2: for \(i=1\) to \(P+1\) do |
3: \({X}^{i}={({x}_{1},{x}_{2},\cdots ,{x}_{N})}^{T}.\) |
4: \({Y}^{i}={({y}_{1},{y}_{2},\cdots ,{y}_{N})}^{T}.\) |
5: end for |
6: \(X\in {R}^{N\times P}\mathop{\to }\limits^{QR\,decomposition}[{S}_{1},{S}_{2}][\begin{array}{c}{R}_{1}\\ 0\end{array}]\) |
7: for \(i=1\) to \(N\) do |
8: \({B}^{i}\mathop{\leftarrow }\limits^{CS\,reconstruction\,algorithm}({{{\rm{S}}}_{2}}^{T}* {Y}^{i},{{{\rm{S}}}_{2}}^{T}{* U}^{T}).\) |
9: end for |
10: \({B}_{i}\to {A}_{i}\) |
11: \(A=[{A}^{1},{A}^{2},\cdots ,{A}^{N}]\in {R}^{N}.\) |
12: return A. |