Numerical Analysis in Nonlinear Least Squares Methods and Applications
Access Status
Open access
Authors
Eu, Christina Nguk Ling
Date
2017Supervisor
Prof. Bean San Goh
Type
Thesis
Award
MPhil
Metadata
Show full item recordFaculty
Engineering and Science (Sarawak)
School
Electrical and Computer Engineering
Collection
Abstract
The approximate greatest descent (AGD) method and a two-phase AGD method (AGDN) are proposed as new methods for a nonlinear least squares problem. Numerical experiments show that these methods outperform existing methods including the Levenberg-Marquardt method. However, the AGDN method outperforms the AGD method with a faster convergence. If the AGDN method fails due to singularity of the Hessian matrix, the AGD method should be used.
Related items
Showing items related by title, author, creator and subject.
-
Chow, Chi Ngok (2010)The largest wool exporter in the world is Australia, where wool being a major export is worth over AUD $2 billion per year and constitutes about 17 per cent of all agricultural exports. Most Australian wool is sold by ...
-
Woloszynski, T.; Podsiadlo, P.; Stachowiak, Gwidon (2015)Efficient numerical methods are essential in the analysis of finite hydrodynamic bearings with surface texturing. This is especially evident in optimization and parametric studies where the discretization and integration ...
-
Grigoleit, Mark Ted (2008)The Constrained Shortest Path Problem (CSPP) consists of finding the shortest path in a graph or network that satisfies one or more resource constraints. Without these constraints, the shortest path problem can be solved ...