Now showing items 1-2 of 2

  • Fuzzy-neural networks for medical diagnosis 

    Authors:Şenol, Canan; Yıldırım, Tülay
    Publisher and Date:(2010)
    In this paper a novel fuzzy-neural network architecture is proposed and the algorithm is developed. Using this new architecture fuzzy-CSFNN fuzzy-MLP and fuzzy-RBF configurations were constituted and their performances have been compared on medical diagnosis problems. Here conic section function neural network (CSFNN) is also a hybrid neural network structure that unifies the propagation rules of multilayer perceptron (MLP) and radial basis function (RBF) neural networks at a unique network by its ...

  • Signature verification using conic section function neural network 

    Authors:Şenol, Canan; Yıldırım, Tülay
    Publisher and Date:(Springer-Verlag Berlin, 2005)
    This paper presents a new approach for off-line signature verification based on a hybrid neural network (Conic Section Function Neural Network-CSFNN). Artificial Neural Networks (ANNs) have recently become a very important method for classification and verification problems. In this work CSFNN was proposed for the signature verification and compared with two well known neural network architectures (Multilayer Perceptron-MLP and Radial Basis Function-RBF Networks). The proposed system was trained ...