Global Search Methods for Solving Nonlinear Optimization Problems
Shang, Yi
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Permalink
https://hdl.handle.net/2142/81906
Description
Title
Global Search Methods for Solving Nonlinear Optimization Problems
Author(s)
Shang, Yi
Issue Date
1997
Doctoral Committee Chair(s)
Wah, Benjamin W.
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Computer Science
Language
eng
Abstract
We show experimental results in applying Novel to solve nonlinear optimisation problems, including (a) the learning of feedforward neural networks, (b) the design of quadrature-mirror-filter digital filter banks, (c) the satisfiability problem, (d) the maximum satisfiability problem, and (e) the design of multiplierless quadrature-mirror-filter digital filter banks. Our method achieves better solutions than existing methods, or achieves solutions of the same quality but at a lower cost.
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