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In this document, we will describe alternative versions of SAILnet \cite{Zylberberg_2011} which address the convergence issues present in the original. The first section \ref{descend} will briefly sketch the sparse approximation equations obtained when the membrane potentials in SAILnet are interpreted as continuous coefficients in our sparse coding model. In section \ref{thresh}, we will introduce a thresholding approach to maintain neurally plausible properties but also descend the reconstruction, sparsity and decorrelation objective in a similar manner to Rozell's LCA \cite{Rozell_2008}. Finally, Then,  in section \ref{spike}, we will show that a spiking version of our Rate-based Sparse and Independent Local network will converge is guaranteed  to descend  the appropriate sparse coefficients objective function  \cite{Shapero_13}.