A Radical-Partitioned Neural Network System Using a Modified Sigmoid Function and a Wight-Dotted Radical Selector for Large-Volume Chinese Characters Recognition VLSI
نویسندگان
چکیده
This paperpnsenb a radical-partitioned neural network system using a modified Sigmoid fvnction and a weight-dotted radical selector f o r large-volume Chinese characters recognition VLSI. Wiih 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 compand t o the system without it.
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