Discriminant analysis based on lifting wavelet transform and learning vector quantization
基于提升小波变换与学习矢量量化网络的鉴别分析方法

A new discriminant analysis method based on LWT(Lifting Wavelet Transform) and LVQ(Learning Vector Quantization) Network was proposed in this paper.LWT is faster and more efficient than the first generation wavelet transform,but it also has the multi-resolution characteristics.LWT can be used to extract the low frequency coefficients and reduce the dimension of an image.LVQ is an effective learning algorithm that trains the competitive layer under supervision.It has a simple network structure,but it also has good discriminant analysis ability.The experimental results on ORL face database show that the method proposed has very good classification capability and high recognition rate.