Abstract—This paper presents the analysis of the learning rate using the Counter Propagation network (CPN) algorithm for the hand written characters recognition application. The recognition process uses the forward only CPN algorithm to recognize the hand written characters. The experimental results obtained with different learning rate values shows that learning rate has large effect on the recognition process. Upper-case English alphabets for a number of different styles gathered from different peoples are used in the analysis for the performance of the CPN algorithm. The obtained recognition rates were 60% to 98% using the CPN for different learning rate value. The experimental results are very encouraging and satisfactory.
Index Terms—Handwritten character recognition, counter propagation networks, learning rate, performance.
W. H. Bangyal is with the Department of Computing and Technology Iqra University Islamabad, Pakitsan (e-mail: waqas_bangyal@hotmail.com). J. Ahmad is with Abasyn University Peshawar, Pakistan (e-mail: jamil. ahmad@abasyn. edu.pk).
Q. Abbas is with the Department of Computing and Technology Iqra University Islamabad, Pakistan (e-mail: qamar.bhk@gmail.com).
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Cite:W. H. Bangyal, J. Ahmad, and Q. Abbas, "Analysis of Learning Rate Using CPN Algorithm for Hand Written Character Recognition Application," International Journal of Engineering and Technology vol. 5, no. 2, pp. 187-190, 2013.
