caa a22 4500 463244915 CHVBK 20180405153323.0 cr unu---uuuuu 170326e20070901xx s 000 0 eng 10.1007/s00422-007-0169-x doi (NATIONALLICENCE)springer-10.1007/s00422-007-0169-x An extended model for a spiking neuron class [Elektronische Daten] [Ana Guerreiro, Carlos Paz de Araujo] This paper proposes an extension to the model of a spiking neuron for information processing in artificial neural networks, developing a new approach for the dynamic threshold of the integrate-and-fire neuron. This new approach invokes characteristics of biological neurons such as the behavior of chemical synapses and the receptor field. We demonstrate how such a digital model of spiking neurons can solve complex nonlinear classification with a single neuron, performing experiments for the classical XOR problem. Compared with rate-coded networks and the classical integrate-and-fire model, the trained network demonstrated faster information processing, requiring fewer neurons and shorter learning periods. The extended model validates all the logic functions of biological neurons when such functions are necessary for the proper flow of binary codes through a neural network. Springer-Verlag, 2007 Guerreiro Ana Department of Computer Engineering, Federal University of Rio Grande do Norte, 59078, Natal, RN, Brazil aut Paz de Araujo Carlos Department of Electrical and Computer Engineering, University of Colorado at Colorado Springs, 80918, Colorado Springs, CO, USA aut Biological Cybernetics Springer-Verlag 97/3(2007-09-01), 211-219 0340-1200 97:3<211 2007 97 422 https://doi.org/10.1007/s00422-007-0169-x text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00422-007-0169-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Guerreiro Ana Department of Computer Engineering, Federal University of Rio Grande do Norte, 59078, Natal, RN, Brazil aut NATIONALLICENCE 700 1- Paz de Araujo Carlos Department of Electrical and Computer Engineering, University of Colorado at Colorado Springs, 80918, Colorado Springs, CO, USA aut NATIONALLICENCE 773 0- Biological Cybernetics Springer-Verlag 97/3(2007-09-01), 211-219 0340-1200 97:3<211 2007 97 422 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer