信息与控制2011，Vol.40Issue(3)：375-380,6.DOI:10.3724/SP.J.1219.2011.00375
基于组合特征和PSO-BP算法的数字识别
Digital Recognition Based on Combined Feature and PSO-BP Algorithm
摘要
Abstract
A new method of digital recognition based on combined features and PSO-BP (particle swarm optimization -backpropagation) algorithm is presented. The combined feature vectors of digital image are composed of grid feature, projection feature and structural features of Euler number in accordance with the feature weight coefficients. By applying PSO-BP neural network to recognition, it gives full play to global optimization capability of the particle swarm algorithm and local search advantages of BP algorithm. Experimental results show that this method is of high recognition rate, fast network convergence speed and high precision.关键词
组合特征/粒了群算法/BP神经网络/数字识别Key words
combined feature/ PSO (particle swarm optimization) algorithm/ BP (backpropagation) neural network/ digital recognition分类
信息技术与安全科学引用本文复制引用
罗勇,和小娟..基于组合特征和PSO-BP算法的数字识别[J].信息与控制,2011,40(3):375-380,6.基金项目
河南省自然科学基金资助项目(2009B510015). （2009B510015）
