Fig. 1.

Figure (a) shows fixed-point iterative rule of the proposed MOL algorithm from (14) and (b) shows the architecture of the five-layer CNN ${𝓗}_{\theta }(\cdot )$ used in the experiments. When $\alpha =1$, the approach reduces to the MoDL [16], which was originally introduced for unrolled optimization, or RED [8], which was introduced for PnP models. Our analysis shows that using $\alpha =1$ in the DEQ setting requires highly constrained networks for convergence, which translates to poor performance.