Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

Coded block neural network VLSI system using an adaptive learning-rate technique to train chinese character patterns

Coded block neural network VLSI system using an adaptive learning-rate technique to train chinese character patterns

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
Electronics Letters — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

A coded block neural network VLSI system is presented that uses an adaptive learning-rate technique to train Chinese character patterns. Using the adaptive learning-rate technique, 500 Chinese characters have been successfully trained in 47.2 h using a 28 MIPs computer.

References

    1. 1)
      • B. Widrow , R.G. Winter , R.A. Baxter . Layered neural nets for pattern recognition. IEEE Trans. , 1109 - 1117
    2. 2)
      • G. Mirchandani , W. Cao . On hidden nodes for neural nets. IEEE Trans.
    3. 3)
      • Kuo, J.B., Mao, W.C.: `Adaptive neural network structure with coded local blocks for pattern recognition VLSI', Proc. 1991, IJCNN.
    4. 4)
      • D.S. Touretzky , D.A. Pomerleau . What's hidden in the hidden layers. Neural networks
    5. 5)
      • W.P. Jones , J. Hoskins . Back-propagation: a generalized delta learning rule. Byte , 155 - 162
    6. 6)
      • Kuo, J.B.: `A coded block adaptive block neural network structure for pattern recognition VLSI', Dig. 1991 Int. Symp. on VLSI Tech. Sys. and Applications.
    7. 7)
      • T.P. Vogl , J.K. Mangis , A.K. Rigler . Accelerating the convergence of the back propagation method. Biol. Cybern. , 129 - 263
    8. 8)
      • –DARPA Neural Network Study–, October 1987–February 1988.
    9. 9)
      • Yamada, K., Kami, H., Tsukumo, J., Temma, T.: `Handwritten numerical recognition by multi-layered neural network with improved learning algorithm', Int. Joint Conf. of Neural Networks, 1989.
    10. 10)
      • M.W. Mao , J.B. Kuo . A coded block adaptive neural network system with a radical-partitioned structure for large-volume Chinese character recognition. Neural networks
    11. 11)
      • D.E. Rumelhart , J. McClelland . (1986) , Parallel distribution processing.
http://iet.metastore.ingenta.com/content/journals/10.1049/el_19921244
Loading

Related content

content/journals/10.1049/el_19921244
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address