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.
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References
Duan M, He Y (2010) Handwritten alphabet recognition based on LVQ neural network. J Jishou Univ 31(2):41
Lv F, Zhu S (2005) Recognition of letters with noise based on hopfield neural network. Comput Inf Technol 12:20
Hecht-Nielsen R (1991) Neurocomputing, vol 1. Addison-Wesley Publishing Co, Reading, pp 95–103
Shen Y, Liu L, Ju X (2011) Handwritten character recognition technology based on CMAC neural network. Digit Technol Appl 2:67
Wang Z (2011) Vehicle license plate recognition base on improved BP network. Microelectron Comput 28(9):66
Xie Z, Shang L, Wang J (2011) A survey combination of rough set and neural. Network 1:1371
Yu H, Wu W-Q, Cao L (2009) The improves on the standard BP algorithm and their use. Comput Knowl Technol 5(19):5256
Zhu K, Wang Z (2010) Proficient in MATLAB neural network, vol 1, Publishing House of Electronics Industry, Beijing, p 209
Cong S, Lu T (2006) Design of three artificial neural networks used on English character recognition. Chin J Sci Instrum 27(6):2242–2244
Wan H, Feng X, Lv M (2008) Application of the improved BP algorithm to the recognition of word with noise. Microcomput Inf 24(30):208
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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Zhou, F., Zhu, X. (2013). Alphabet Recognition Based on Scaled Conjugate Gradient BP Algorithm. In: Yang, Y., Ma, M. (eds) Proceedings of the 2nd International Conference on Green Communications and Networks 2012 (GCN 2012): Volume 1. Lecture Notes in Electrical Engineering, vol 223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35419-9_27
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DOI: https://doi.org/10.1007/978-3-642-35419-9_27
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