Original Contribution: A polynomial time algorithm for the construction and training of a class of multilayer perceptrons

Authors:
Asim Roy;Lark Sang Kim;Somnath Mukhopadhyay
Affiliations:
-;-;-
Venue:
Neural Networks
Year:
1993

Citing 3
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Abstract

This paper presents a polynomial time algorithm for the construction and training of a class of multilayer perceptrons for classification. It uses linear programming models to incrementally generate the hidden layer in a restricted higher-order perceptron. Polynomial time complexity of the method is proven. Computational results are provided for several well-known applications in the areas of speech recognition, medical diagnosis, and target detection. In all cases, very small nets were created that had error rates similar to those reported so far.