Title :
Efficient and reliable training of neural networks
Author :
Yu, Hao ; Wilamowski, Bogdan M.
Author_Institution :
Electr. & Comput. Eng., Auburn Univ., Auburn, AL
Abstract :
This paper introduces a neural network training tool, NBN 2.0, which is developed based on neuron by neuron computing method. 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 Web site.
Keywords :
C++ language; learning (artificial intelligence); neural nets; visual programming; C++ language; Levenberg Marquardt algorithm; NBN 2.0; Visual Studio platform; arbitrarily connected neuron network; error backpropagation algorithm; neural network training; neuron computing method; Application software; Backpropagation algorithms; Computer networks; Industrial training; Jacobian matrices; Multilayer perceptrons; Network topology; Neural networks; Neurons; Software tools; neural networks; training tool;
Conference_Titel :
Human System Interactions, 2009. HSI '09. 2nd Conference on
Conference_Location :
Catania
Print_ISBN :
978-1-4244-3959-1
Electronic_ISBN :
978-1-4244-3960-7
DOI :
10.1109/HSI.2009.5090963
