DocumentCode
3535832
Title
Off-line handwritten digit recognition based on improved BP artificial neural network
Author
Zhang, Chengde ; Huang, Xiangnian
Author_Institution
Sch. of Math. & Comput. Eng., Xihua Univ., Chengdu
Volume
1
fYear
2008
fDate
12-15 Oct. 2008
Firstpage
626
Lastpage
629
Abstract
This paper improved the adaptive factor of gradient to improve the transfer function on the base of the means of momentum, aimed at the training difficult to escape the flat area of error. This method had an application on off-line handwritten recognition. The results showed: this method could not only raise precision of BP artificial neural network, but also improve the convergent speed of it.
Keywords
handwriting recognition; neural nets; improved BP artificial neural network; off-line handwritten digit recognition; transfer function; Artificial neural networks; Character recognition; Computer errors; Computer networks; Convergence; Handwriting recognition; Mathematics; Neurons; Presses; Transfer functions; BP artificial neural network; factor of gradient; off-line handwritten digit recognition; transfer function;
fLanguage
English
Publisher
ieee
Conference_Titel
Service Operations and Logistics, and Informatics, 2008. IEEE/SOLI 2008. IEEE International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-2012-4
Electronic_ISBN
978-1-4244-2013-1
Type
conf
DOI
10.1109/SOLI.2008.4686473
Filename
4686473
Link To Document