%0 Journal Article %A Jamal Fathi Abu Hasna %D 2008 %J International Journal of Electrical and Computer Engineering %B World Academy of Science, Engineering and Technology %I Open Science Index 20, 2008 %T Signature Recognition Using Conjugate Gradient Neural Networks %U https://publications.waset.org/pdf/765 %V 20 %X There are two common methodologies to verify signatures: the functional approach and the parametric approach. This paper presents a new approach for dynamic handwritten signature verification (HSV) using the Neural Network with verification by the Conjugate Gradient Neural Network (NN). It is yet another avenue in the approach to HSV that is found to produce excellent results when compared with other methods of dynamic. Experimental results show the system is insensitive to the order of base-classifiers and gets a high verification ratio. %P 1698 - 1702