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A comparison of training techniques : ADALINE, back propagation and genetic algorithms

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A comparison of training techniques : ADALINE, back propagation and genetic algorithms

Yang, Wei (2000) A comparison of training techniques : ADALINE, back propagation and genetic algorithms. Other thesis, Concordia University.

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Abstract

This study is in the area of neural network architectures and training algorithms. The emphasis is placed on the comparisons of ADALINE, Back Propagation and Genetic Algorithms in training neural networks. Concrete examples are developed to illustrate and reveal the fundamental theories of neural networks, and demonstrate the strengths and weaknesses of ADALINE, Back Propagation and Genetic Algorithms. An object-oriented approach is applied in the overall analysis and design of the neural network architectures. The Object-oriented programming with C++ is used to facilitate the development and implementation of the neural network architectures and training algorithms.

Divisions:Concordia University > Faculty of Engineering and Computer Science > Computer Science and Software Engineering
Item Type:Thesis (Other)
Authors:Yang, Wei
Pagination:vii, 120 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:Major reports (M.Comp.Sc.)
Program:Computer Science and Software Engineering
Date:2000
Thesis Supervisor(s):Grogono, Peter
ID Code:1107
Deposited By:Concordia University Libraries
Deposited On:27 Aug 2009 13:16
Last Modified:08 Dec 2010 10:18
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