基于改进BP神经网络的手写体数字识别  

Handwritten Numeral Recognition Based on the Improved BP Neural Network

作　　者：何松[1] 戚建宇[2] 

机构地区：[1]常州工学院计算机信息工程学院,常州213002 [2]常州工学院延陵学院,常州213002

出　　处：《计算机科学》2011年第B10期204-205,248,共3页Computer Science

摘　　要：数字识别在许多领域有广泛的应用。通过对人工神经网络的研究与学习,运用改进的BP神经网络对无约束手写体数字识别过程中的数字样本进行识别。实验证明,该方法具有很强的抗干扰性,克服了传统BP算法的局限性,其识别率和准确率都有很大提高。The digital recognitions have extensive application in a lot of important fields.The artificial network was studied in the paper.The figure specimens were filtered through the process of unconstrained handwritten numeral,that it was recognized by the improved BP neural network.The result of experiment demonstrates that the method has very high noise immunity capacity and overcomes the limitation of traditional BP algorithm.The recognition rate and precision rate are greatly improved at the same time.

关 键 词：神经网络 数字识别 改进BP网络 

分 类 号：TP391.43[自动化与计算机技术—计算机应用技术]