This paper describes a fall-back procedure for use with the Gauss-Newton method for non-linear least-squares problems. While the basic Gauss-Newton algorithm is often success-ful, it is well-known that it can sometimes generate poor search directions and exhibit slow convergence. For dealing with such situations we suggest a new two-dimensional search strategy. Numerical experiments indicate that the proposed technique can be effective.
An optimization problem that does not have an unique local minimum is often very difficult to solve....
In this paper, we present a brief survey of methods for solving nonlinear least-squares problems. We...
Adaptive Least Squares Matching (ALSM) is a powerful technique for precisely locating objects in dig...
Original article can be found at: http://www.ici.ro/camo/journal/jamo.htmThis paper describes a fall...
This paper has two main purposes: To discuss general principles for a reliable and efficient numeric...
We propose a modification of an algorithm introduced by Martínez (1987) for solving nonlinear least-...
Abstract. In this paper, a Gauss-Newton method is proposed for the solution of large-scale nonlinear...
In this work, a new stabilization scheme for the Gauss-Newton method is defined, where the minimum n...
Abstract. In this paper, a Gauss-Newton method is proposed for the solution of large-scale nonlinear...
In this paper, a Gauss-Newton method is proposed for the solution of large-scale nonlinear least-squ...
In this paper, a Gauss-Newton method is proposed for the solution of large-scale nonlinear least-squ...
The Adaptive Least Squares Matching (ALSM) problem of Gruen is conventionally described as a statist...
Abstract. In this paper, a Gauss-Newton method is proposed for the solution of large-scale nonlinear...
This work addresses a spectral correction for the Gauss-Newton model in the solution of nonlinear le...
Abstract. Modeling the mean of a random variable as a function of unknown parameters leads to a nonl...
An optimization problem that does not have an unique local minimum is often very difficult to solve....
In this paper, we present a brief survey of methods for solving nonlinear least-squares problems. We...
Adaptive Least Squares Matching (ALSM) is a powerful technique for precisely locating objects in dig...
Original article can be found at: http://www.ici.ro/camo/journal/jamo.htmThis paper describes a fall...
This paper has two main purposes: To discuss general principles for a reliable and efficient numeric...
We propose a modification of an algorithm introduced by Martínez (1987) for solving nonlinear least-...
Abstract. In this paper, a Gauss-Newton method is proposed for the solution of large-scale nonlinear...
In this work, a new stabilization scheme for the Gauss-Newton method is defined, where the minimum n...
Abstract. In this paper, a Gauss-Newton method is proposed for the solution of large-scale nonlinear...
In this paper, a Gauss-Newton method is proposed for the solution of large-scale nonlinear least-squ...
In this paper, a Gauss-Newton method is proposed for the solution of large-scale nonlinear least-squ...
The Adaptive Least Squares Matching (ALSM) problem of Gruen is conventionally described as a statist...
Abstract. In this paper, a Gauss-Newton method is proposed for the solution of large-scale nonlinear...
This work addresses a spectral correction for the Gauss-Newton model in the solution of nonlinear le...
Abstract. Modeling the mean of a random variable as a function of unknown parameters leads to a nonl...
An optimization problem that does not have an unique local minimum is often very difficult to solve....
In this paper, we present a brief survey of methods for solving nonlinear least-squares problems. We...
Adaptive Least Squares Matching (ALSM) is a powerful technique for precisely locating objects in dig...