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A radical-partitioned neural network system using a modified sigmoid function and a weight-dotted radical selector for large-volume Chinese character recognition VLSI

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3 Author(s)
Kuo, J.B. ; Dept. of Electr. Eng., Nat. Taiwan Inst. of Technol., Taipei, Taiwan ; Chen, D.Y. ; Mao, M.W.

This paper presents a radical-partitioned neural network system using a modified sigmoid function and a weight-dotted radical selector for large-volume Chinese characters recognition VLSI. With a modified sigmoid function and the weight-dotted radical selector, the recognition rate of 1000 radical-partitioned Chinese characters can be enhanced to 90% from 70% for the input samples with 15% random errors as compared to the system without it

Published in:

Circuits and Systems, 1994. ISCAS '94., 1994 IEEE International Symposium on  (Volume:6 )

Date of Conference:

30 May-2 Jun 1994