Efficient and reliable training of neural networks

Authors:
Hao Yu;Bogdan M. Wilamowski
Affiliations:
Electrical and Computer Engineering, Auburn University, Alabama;Electrical and Computer Engineering, Auburn University, Alabama
Venue:
HSI'09 Proceedings of the 2nd conference on Human System Interactions
Year:
2009

Citing 8
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Abstract

This paper introduces a neural network training tool, NBN 2.0, which is developed based on neuron by neuron computing method [1][2]. Error backpropagation (EBP) algorithm, Levenberg Marquardt (LM) algorithm and its improved versions are implemented in two different computing methods, traditional forward-backward computation and newly developed forward-only computation. The software can handle not only conventional multilayer perceptron (MLP) networks, but also arbitrarily connected neuron (ACN) networks. Several examples are presented to explain how to use this tool for neural network training. The software is developed based on Visual Studio platform using C++ language and it is available for everyone on the website.