Abstract
In this paper we explore the Izhikevich spiking neuron model especially the synergy of the dimensionless model parameters and their implications to the spiking of the neuron itself. This spiking, principally the spike rate, is highly important from the application point of view. The understanding of the model is useful for better spiking network design, when the input neuronal stimulus is transferred to the spikes in order to produce faster network response. Whereas we can achieve the better neuronal response of the spiking network through utilization of the correct model parameters which impact to the neurons and the network neuronal dynamics significantly. The model parameters setup were described, demonstrated and spiking neuron model output and behaviour examined. The influence of the input current was also described in a given experimental study.
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Acknowledgments
The research described here has been financially supported by University of Ostrava grant SGS07/PrF/2017. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not reflect the views of the sponsors.
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Barton, A., Volna, E., Kotyrba, M. (2019). The Application Perspective of Izhikevich Spiking Neural Model – The Initial Experimental Study. In: Matoušek, R. (eds) Recent Advances in Soft Computing . MENDEL 2017. Advances in Intelligent Systems and Computing, vol 837. Springer, Cham. https://doi.org/10.1007/978-3-319-97888-8_19
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DOI: https://doi.org/10.1007/978-3-319-97888-8_19
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Online ISBN: 978-3-319-97888-8
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