基于BP神经网络的手写字符识别系统

Handwritten Character Recognition System Based on BP Neural Network

基于BP神经网络对非线性系统辨识的通用性和自适应性等特点,构建了一个BP神经网络模型,增强了网络的自适应能力和学习能力,提高了网络的精度和收敛速度,并在此基础上开发出一个高效准确的手写体字符识别系统.

Based on the features of BP neural network to the identification of nonlinear systems and adaptability,a BP neural network model is built to increase the network＇s capacity and adaptive learning capabilities of the network, and to improve the accuracy and speed of convergence. Furthermore, an efficient and accurate handwriting character recognition system is developed on this basis.