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Gradient methods have applications in multiple fields, including signalprocessing, image processing, and dynamic systems. In this paper, we present anonlinear gradient method for solving convex supra-quadratic functions bydeveloping the search direction, that done by hybridizing between the twoconjugate coefficients HRM [2] and NHS [1]. The numerical results proved theeffectiveness of the presented method by applying it to solve standard problemsand reaching the exact solution if the objective function is quadratic convex.Also presented in this article, an application to the problem of named entitiesin the Arabic medical language, as it proved the stability of the proposedmethod and its efficiency in terms of execution time.

Using a New Nonlinear Gradient Method for Solving Large Scale Convex Optimization Problems with an Application on Arabic Medical Text