Recursive dynamic node creation in multilayer neural networks

Date
1993
Authors
Trujillo, Frank O., author
Sheedvash, Sassan, author
Azimi-Sadjadi, Mahmood R., author
IEEE, publisher
Journal Title
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Abstract
This paper presents the derivations of a novel approach for simultaneous recursive weight adaptation and node creation in multilayer back-propagation neural networks. The method uses time and order update formulations in the orthogonal projection method to derive a recursive weight updating procedure for the training process of the neural network and a recursive node creation algorithm for weight adjustment of a layer with added nodes during the training process. The proposed approach allows optimal dynamic node creation in the sense that the mean-squared error is minimized for each new topology. The effectiveness of the algorithm is demonstrated on several benchmark problems, namely, the multiplexer and the decoder problems as well as a real world application for detection and classification of buried dielectric anomalies using a microwave sensor.
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Subject
backpropagation
feedforward neural nets
topology
Citation
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