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Title:Global Search Methods for Solving Nonlinear Optimization Problems
Author(s):Shang, Yi
Doctoral Committee Chair(s):Wah, Benjamin W.
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Computer Science
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.
Issue Date:1997
Type:Text
Language:English
Description:288 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997.
URI:http://hdl.handle.net/2142/81906
Other Identifier(s):(MiAaPQ)AAI9812765
Date Available in IDEALS:2015-09-25
Date Deposited:1997


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