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View all- Renka R(2013)Nonlinear least squares and Sobolev gradientsApplied Numerical Mathematics10.1016/j.apnum.2012.12.00265(91-104)Online publication date: 1-Mar-2013
In general, when a quasi-Newton method is applied to solve a system of nonlinear equations, the quasi-Newton direction is not necessarily a descent direction for the norm function. In this paper, we show that when applied to solve symmetric nonlinear ...
For solving nonlinear programming problems we iteratively minimize the penalty Lagrangian developed by Hestenes, Powell, and Rockafellar with the multipliers estimated by solving nonnegatively constrained quadratic programming subproblems and a penalty ...
We analyze the conjugate gradient (CG) method with variable preconditioning for solving a linear system with a real symmetric positive definite (SPD) matrix of coefficients $A$. We assume that the preconditioner is SPD on each step, and that the ...
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