George, S.Sabari, M.2026-02-052017Applied Mathematics and Computation, 2017, 294, , pp. 169-179963003https://doi.org/10.1016/j.amc.2016.09.009https://idr.nitk.ac.in/handle/123456789/25702Convergence rate result for a modified steepest descent method and a modified minimal error method for the solution of nonlinear ill-posed operator equation have been proved with noisy data. To our knowledge, convergence rate result for the steepest descent method and minimal error method with noisy data are not known. We provide a convergence rate results for these methods with noisy data. The result in this paper are obtained under less computational cost when compared to the steepest descent method and minimal error method. We present an academic example which satisfies the assumptions of this paper. © 2016 Elsevier Inc.ErrorsMathematical operatorsNonlinear equationsComputational costsConvergence ratesDiscrepancy principleIll-posed operator equationMinimal errorsNonlinear ill-posed equationsNonlinear ill-posed problemsRegularization methodsSteepest descent method