A radical-partitioned coded block adaptive neural network structure for large-volume Chinese characters recognition
James B. Kuo, M.W. Mao · 2003
A coded block adaptive neural network system using a radical-partitioned structure for a large-volume Chinese character recognition VLSI is presented. Using this coded block adaptive neural network system, 1000 frequently used Chinese characters have been successfully trained in 139.2 h using a 18-MIPS computer. Based on the simulation results, the coded block system with a radical-partitioned structure provided an acceptable learning time, a good recognition rate, and an excellent expansion capability for large-volume Chinese character recognition using a VLSI.>