一种改进的反向传播神经网络算法

Journal of Applied Sciences ›› 2004, Vol. 22 ›› Issue (3): 384-387.

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An Improved Back-Propagation Neural Network Algorithm

QIU Hao¹, WANG Dao-bo², ZHANG Huan-chun¹

1. Department of Testing and Measurement Engineering, College of Automation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
2. Aeronautic Simulation and Control Lab, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Received:2003-04-21 Revised:2003-06-10 Online:2004-09-30 Published:2004-09-30

Abstract

Abstract: Based on the idea of standard back-propagation(BP) learning algorithm, an improved BP learning algorithm is presented. Three parameters are incorporated into each processing unit(PU) to enhance the output function. The improved BP learning algorithm is developed for updating the three parameters as well as the connection weights. It not only improves the learning speed, but also reduces the occurrence of local minima. Finally, the algorithm is tested on the XOR problem to verify the validity of the improved BP.

Key words: neural networks, back-propagation, algorithm, simulation

CLC Number:

TP18
TP391.9

QIU Hao, WANG Dao-bo, ZHANG Huan-chun. An Improved Back-Propagation Neural Network Algorithm[J]. Journal of Applied Sciences, 2004, 22(3): 384-387.

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An Improved Back-Propagation Neural Network Algorithm

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