Aiming at the problems of gradient vanishing in recognition of off-line handwritten Chinese characters using convolutional neural network

a recognition approach based on knowledge transfer with feedback is given.Convolutional neural network is decomposed into a main network and several sub-networks

network parameters are transfered to networks with less layers. Chinese character samples are segmented and sent to sub-networks for training by type structure

then knowledge of several sub-network are transferred to main-network by knowledge transfer. Adjust the weight coefficient of sub-networks adaptively with feedback theory

to realize knowledge integration of the whole network. Simulation result shows that this approach relieves gradient vanishing effectively and has higher recognition rate.