A One-Parameter Memoryless DFP Algorithm for Solving System of Monotone Nonlinear Equations with Application in Image Processing

In matrix analysis, the scaling technique reduces chances of an ill-conditioning matrix. This article proposes a one-parameter memoryless Davidon–Fletcher–Powell (DFP) algorithm for solving system monotone nonlinear equations with convex constraints. The measure function that involves all eigenvalues DFP is minimized to obtain parameter’s optimal value. resulting and derivative-free low memory requirements globally convergent under some mild conditions. A numerical comparison showed efficient in terms number iterations, evaluations, CPU time. performance further illustrated by problems arising from image restoration.