Recognition of Paper Currency Research Based on AGA-BP Neural Network

Article Preview

Abstract:

The genetic algorithm is a randomized search method for a class of reference biological evolution of the law evolved, with global implicit parallelism inherent and better optimization. This paper presents an adaptive genetic algorithm to optimize the use of BP neural network method, namely the structure of weights and thresholds to optimize BP neural network to achieve the recognition of banknotes oriented. Experimental results show that after using genetic algorithms to optimize BP neural network controller can accurately and quickly achieved recognition effect on banknote recognition accuracy compared to traditional BP neural network has been greatly improved, improved network adaptive capacity and generalization ability.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 989-994)

Pages:

3968-3972

Citation:

Online since:

July 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Kong Fanhui. Research-oriented high-speed sorter RMB Par recognition technology [D]. Harbin Institute of Technology master's degree in theory Man, 2004: 30-35.

Google Scholar

[2] Cui Mingxing. Research banknote recognition algorithm [D]. Harbin Industrial University, a master's degree thesis, 2002: 22-27.

Google Scholar

[3] Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins. Digital image processing [M]. Electronic Industry Press . 2009: 117-121.

Google Scholar

[4] Wei Zhengyi. Study notes image recognition algorithm [D]. Harbin Polytechnic University master's degree thesis, (2009).

Google Scholar

[5] Cao Buqing. Based Currency Recognition GA evolution BP neural network [D]. Zhongnan University graduate dissertations pack, (2007).

Google Scholar