“…In [20], it was shown that many convex minimization and monotone inclusion problems reduce to the more general problem of finding a fixed point of compositions of averaged operators, which provided a unified analysis of various proximal splitting algorithms. Along these lines, several fixed point methods based on various combinations of averaged operators have since been devised, see [1,2,5,9,11,13,14,17,18,24,25,38,46] for recent work. Motivated by deep neural network structures with thus far elusive asymptotic properties, we investigate in the present paper a novel averaged operator model involving a mix of nonlinear and linear operators.…”