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University of Illinois at Urbana-Champaign
Global Search Methods for Solving Nonlinear Optimization Problems
Abstract
dc:descriptionWe 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.
Degree
thesis:*- Name thesis:degree_name
- Ph.D.
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Computer Science
- Grantor
- University of Illinois at Urbana-Champaign
- Year dc:date
- 2015
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Shang, Yi
- Contributors dc:contributor
-
- Wah, Benjamin W.
Subjects
dc:subject × 1Rights
- Language dc:language
- eng
Identifiers
dc:identifier.*- Identifier
- (MiAaPQ)AAI9812765
- OAI identifier oai:identifier
- oai:www.ideals.illinois.edu:2142/81906