【摘要】 该文分析了手写签名样本的特征值在特征空间上的分布。在此基础上,直接从神经元分类功能的物理意义出发,设计了具有非线性边界的,用于手写签名认证的神经网络分类器,妥善地解决了实际应用中,由于真实签名样本数量少和伪签名样本缺乏,不能训练神经网络的问题,取得了较好的认证结果。更多还原

【Abstract】 In this paper the distribution of the feature vectors of signatures is analyzed.In light of the distribution’s characteristics,a simple nonlinear neural network classifier is designed.The neural network’s connection weights are de-termined directly from the physical meaning of the classifying edge,so the problem caused by the lack of training sam-ples is avoid.This classifier is applied to the signature verification,and a good correct rate is obtained.更多还原