文档介绍：1
A Brief Description of the
Levenberg-Marquardt Algorithm Implemened
by levmar
Manolis I. A. Lourakis
Institute of Computer Science
Foundation for Research and Technology - Hellas (FORTH)
Vassilika Vouton, . Box 1385, GR711 10
Heraklion, Crete, GREECE
February 11, 2005
Abstract
The Levenberg-Maiquardt (LM) algorithm is an iterative technique that locates the minimum of a function that is expressed as the sum of squares of nonlinear functions. It has become a standard technique for nonlinear least-squares problems and can be thought of as a combination of steepest descent and the Gauss-Newton method. This dDcumcnt briefly describes the nialiicmalius behind levmar, a free LM C/C++ iinplciiiciilalioii that uun be found at http: //www. ics . forth. gr/ ^lourakis/levmar.
Introduction
The Levenberg-Marquardt (LM) algorithm is an iterative technique that locates the minimum of a multivariate function that is expressed as the sum of squares of non-linear real-valued functions |4, 6|. It has become a standard technique for non-linear least-squares problems [7], widely adopted in a broad spectrum of disciplines. LM can be thought of as a combination of steepest descent and the Gauss-Newton method・ When the current solution is far from the correct one, the algorithm behaves like a steepest descent method: slow, but guaranteed to converge・ When the current solution is cl