Alphabet Recognition Based on Scaled Conjugate Gradient BP Algorithm

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 223)

Abstract

Artificial neural network is a reflection of brain function to some degree. Neural network has adaptive and self-learning ability and gets features by learning from samples. It can also apply the knowledge which is obtained from learning to the recognition of images, text, and so on. To study alphabet recognition, the Scaled Conjugate gradient BP algorithm is used in this chapter. The simulation results show that, this method can effectively identify the English letters with noise. Compared with the standard BP algorithm, the improved BP algorithm can greatly reduce the training times of the network, and its speed of convergence is much faster.

Keywords

BP neural network Conjugate gradient algorithm Alphabet recognition 

Notes

Acknowledgments

Institute Level Key Projects Funded by Beijing Institute of Graphic Communication (E-a-2012-31); Funding Project for Academic Human Resources Development in Institutions of Higher Learning under the Jurisdiction of Beijing Municipality (PHR201107145); Scientific Research Common Program of Beijing Municipal Commission of Education of China (KM201210015011).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Beijing Institute of Graphic CommunicationBeijingChina

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