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简单非线性神经网络分类器及其在签名认证中的应用 被引量:1

Simple Nonlinear Neural Network Classifier and its Application to Sig nature Verification
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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。 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.
出处 《计算机工程与应用》 CSCD 北大核心 2002年第19期88-89,92,共3页 Computer Engineering and Applications
关键词 简单非线性神经网络分类器 签名认证 非线性分类器 Signature Verification,Neural Network,Nonlinear Classifier
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参考文献3

  • 1[1]Martin Hagan.Neural Network Design[M].PWS Publishing Company,1996
  • 2[2]Lee L L,Berger T,Aviczer E.Reliable On-line Human Signature Verification Systems[J].IEEE Trans on Pattern Analysis and Machine Intelligence, 1996; 18 (6): 643~647
  • 3[3]CyberSign Company.http://www.cybersign.com/

同被引文献3

  • 1Daniel Richard Oldham. Biometric Identification for Dynamic Signature Verification Using Time Delay Neural Networks. UMI,2001
  • 2Pawlicki T F. Neural network and their application to handwritten digit recognition. IEEE,ICON2, 1998(2) :34-36
  • 3Keiji Yanada. HandWriten recognition by multilayered neural network with improved learning algorithm. IJCNN - 89,1999 (2) : 23-26

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