First Advisor

George G. Lendaris

Date of Publication


Document Type


Degree Name

Master of Science (M.S.) in Electrical and Computer Engineering


Electrical Engineering


Neural networks (Computer science), Perceptrons, Pattern perception, Geometry -- Data processing



Physical Description

1 online resource (93 p.)


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.


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Persistent Identifier