Sponsor
Portland State University. Department of Electrical Engineering
Advisor
George G. Lendaris
Date of Award
1991
Document Type
Thesis
Degree Name
Master of Science (M.S.) in Electrical and Computer Engineering
Department
Electrical Engineering
Physical Description
1 online resource (93 p.)
Subjects
Neural networks (Computer science), Perceptrons, Pattern perception, Geometry -- Data processing
DOI
10.15760/etd.6126
Abstract
A new approach is proposed which uses a combination of a Backprop paradigm neural network along with some perceptron processing elements performing logic operations to construct a numeric-to-symbolic converter. The design approach proposed herein is capable of implementing a decision region defined by a multi-dimensional, non-linear boundary surface. By defining a "two-valued" subspace of the boundary surface, a Backprop paradigm neural network is used to model the boundary surf ace. An input vector is tested by the neural network boundary model (along with perceptron logic gates) to determine whether the incoming vector point is within the decision region or not. Experiments with two qualitatively different kinds of nonlinear surface were carried out to test and demonstrate the design approach.
Persistent Identifier
http://archives.pdx.edu/ds/psu/24617
Recommended Citation
Tang, Zibin, "A new design approach for numeric-to-symbolic conversion using neural networks" (1991). Dissertations and Theses. Paper 4242.
https://pdxscholar.library.pdx.edu/open_access_etds/4242
10.15760/etd.6126
Description
If you are the rightful copyright holder of this dissertation or thesis and wish to have it removed from the Open Access Collection, please submit a request to pdxscholar@pdx.edu and include clear identification of the work, preferably with URL