dc.contributor.author | Christodoulou, Chris C. | en |
dc.contributor.author | Bugmann, G. | en |
dc.contributor.author | Clarkson, T. G. | en |
dc.contributor.author | Taylor, J. G. | en |
dc.contributor.editor | Mira J. | en |
dc.contributor.editor | Prieto A. | en |
dc.contributor.editor | Cabestany J. | en |
dc.creator | Christodoulou, Chris C. | en |
dc.creator | Bugmann, G. | en |
dc.creator | Clarkson, T. G. | en |
dc.creator | Taylor, J. G. | en |
dc.date.accessioned | 2019-11-13T10:39:15Z | |
dc.date.available | 2019-11-13T10:39:15Z | |
dc.date.issued | 1993 | |
dc.identifier.issn | 0302-9743 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/53708 | |
dc.description.abstract | The Temporal Noisy-Leaky Integrator (TNU) neuron model with additional inhibitory inputs is presented together with its theoretical mathematical basis. The TNU is a biologically inspired hardware neuron which models temporalfeatures of real neurons like the temporal summation of the dendritic postsynaptic response currents of controlled delay and duration and the decay of the somatic potential due to its membrane leak. In addition, it models the stochastic neurotransmitter release by the synapses of real neurons, as pRAMs are used at each input. Using the TNU, we investigated the effect of synaptic integration between excitatory and inhibitory inputs on the transfer function of the neuron. We observed that inhibitory inputs increase the fluctuations of the input current and reduce the slope of the sigmoidal transfer function of the neuron, which highlights one of the differences between biological neurons and formal neurons. © Springer-Verlag Berlin Heidelberg 1993. | en |
dc.source | International Workshop on Artificial Neural Networks, IWANN 1993 | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84947440482&partnerID=40&md5=5d46cb275b1aba47c0368e8050e93ad2 | |
dc.subject | Neural networks | en |
dc.subject | Stochastic systems | en |
dc.subject | Stochastic models | en |
dc.subject | Biologically inspired | en |
dc.subject | Transfer functions | en |
dc.subject | Neurons | en |
dc.subject | Biological neuron | en |
dc.subject | Hardware neuron | en |
dc.subject | Mathematical basis | en |
dc.subject | Neurotransmitter release | en |
dc.subject | Response current s | en |
dc.subject | Synaptic integration | en |
dc.subject | Temporal summation | en |
dc.title | The temporal noisy-leaky integrator neuron with additional inhibitory inputs | en |
dc.type | info:eu-repo/semantics/article | |
dc.description.volume | 686 | |
dc.description.startingpage | 465 | |
dc.description.endingpage | 470 | |
dc.author.faculty | 002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences | |
dc.author.department | Τμήμα Πληροφορικής / Department of Computer Science | |
dc.type.uhtype | Article | en |
dc.description.notes | <p>Sponsors: Catalan CIRIT | en |
dc.description.notes | Spanish CICYT | en |
dc.description.notes | Conference code: 171019 | en |
dc.description.notes | Cited By :1</p> | en |
dc.source.abbreviation | Lect. Notes Comput. Sci. | en |
dc.contributor.orcid | Christodoulou, Chris C. [0000-0001-9398-5256] | |
dc.gnosis.orcid | 0000-0001-9398-5256 | |