Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/60843
Title: An effective result-feedback neural algorithm for handwritten character recognition
Authors: Zhu, X
Hao, Y
Shi, Y
Zhang, D 
Issue Date: 2001
Publisher: Dynamic Publishers
Source: Neural, parallel & scientific computations, 2001, v. 9, no. 2, p. 139-150 How to cite?
Journal: Neural, parallel & scientific computations 
Abstract: In this paper, a new algorithm of handwritten character recognition based on result-feedback is proposed. It is designed as an effective neural network by adding confidence back-propagation and input modification, thus both pre-processing and recognition operations are closely integrated together. The convergence of the algorithm is proved and many experiments show that the error rate in such a result-feedback neural network (RFNN) can be greatly reduced as well as the robust to environmental noise.
URI: http://hdl.handle.net/10397/60843
ISSN: 1061-5369
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

28
Last Week
4
Last month
Checked on Aug 20, 2017

Google ScholarTM

Check



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.