A secant method for nonlinear least-squares minimization

A secant method for nonlinear least-squares minimization

Quasi-Newton methods have played a prominent role, over many years, in the design of effective practical methods for the numerical solution of nonlinear minimization problems and in multi-dimensional zero-finding. There is a wide literature outlining the properties of these methods and illustrating their performance [e.g., [8]]. In addition, most modern optimization libraries house a quasi-Newt...

Least – Squares Method For Estimating Diffusion Coefficient

 Abstract: Determination of the diffusion coefficient on the base of solution of a linear inverse problem of the parameter estimation using the Least-square method is presented in this research. For this propose a set of temperature measurements at a single sensor location inside the heat conducting body was considered. The corresponding direct problem was then solved by the application of the ...

LEAST – SQUARES METHOD FOR ESTIMATING DIFFUSION COEFFICIENT

Determining the diffusion coefficient based on the solution of the linear inverse problem of the parameter estimation by using the Least-square method is presented. A set of temperature measurements at a single sensor location inside the heat conducting body is required. The corresponding direct problem will be solved by an application of the heat fundamental solution.

Constrained Nonlinear Least Squares: A Superlinearly Convergent Projected Structured Secant Method

Numerical solution of nonlinear least-squares problems is an important computational task in science and engineering. Effective algorithms have been developed for solving nonlinear least squares problems. The structured secant method is a class of efficient methods developed in recent years for optimization problems in which the Hessian of the objective function has some special structure. A pr...

A modified secant method for unconstrained minimization