Date of Award
Summer 2010
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Mathematics & Statistics
Program/Concentration
Computational and Applied Mathematics
Committee Director
Hideaki Kaneko
Committee Member
Richard D. Noren
Committee Member
Noam Zeev
Committee Member
Jin Wang
Committee Member
Duc T. Nguyen
Abstract
This dissertation is focused on the varieties of numerical solutions of nonlinear Hammerstein integral equations. In the first part of this dissertation, several acceleration techniques for post-processed solutions of the Hammerstein equation are discussed. The post-processing techniques are implemented based on interpolation and extrapolation. In this connection, we generalize the results in [29] and [28] to nonlinear integral equations of the Hammerstein type. Post-processed collocation solutions are shown to exhibit better accuracy. Moreover, an extrapolation technique for the Galerkin solution of Hammerstein equation is also obtained. This result appears new even in the setting of the linear Fredholm equation.
In the second half of this dissertation, the wavelet-collocation technique of solving nonlinear Hammerstein integral equation is discussed. The main objective is to establish a fast wavelet-collocation method for Hammerstein equation by using a 'linearization' technique. The sparsity in the Jacobian matrix takes place in the fast wavelet-collocation method for Hammerstein equation with smooth as well as weakly singular kernels. A fast algorithm is based upon the block truncation strategy which was recently proposed in [10]. A multilevel augmentation method for the linearized Hammerstein equation is subsequently proposed which further accelerates the solution process while maintaining the order of convergence. Numerical examples are given throughout this dissertation.
Rights
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DOI
10.25777/c2rv-qw02
ISBN
9781124291567
Recommended Citation
Neamprem, Khomsan.
"Post-Processing Techniques and Wavelet Applications for Hammerstein Integral Equations"
(2010). Doctor of Philosophy (PhD), Dissertation, Mathematics & Statistics, Old Dominion University, DOI: 10.25777/c2rv-qw02
https://digitalcommons.odu.edu/mathstat_etds/32