一种新的基于模糊RBF神经网络的人脸识别方法

A New Face Recognition Method Based on Fuzzy RBF Neural Nerwork

对基于模糊RBF神经网络的人脸图像分类器进行研究。模糊RBF神经网络一般采用BP算法进行学习,收敛速度慢,因此本文提出了一种改进的Levenberg-Marquart优化算法(简称L-M算法)对神经网络进行学习,改进的L-M算法在学习次数和准确度方面都优于BP算法。在ORL人脸图像库上的实验结果表明了此方法的有效性。

A study on classifier of face images based on fuzzy RBF neural network was presented.BP learning algorithm is widely applied in fuzzy RBF neural network,which has the low rate of convergence,therefore,an improved learning algorithm named Levenberg-Marquart（L-M） for fuzzy RBF neural network was proposed and showed effectively in the number of learning and the rate of accuracy.Experimental results on the ORL face database demonstrate the effectiveness of the proposed method.