In this paper, the network transmission properties of a feedforward Spiking Neural Network (SNN) affected by synchronous stimuli are investigated with respect to the connection probability and the synaptic strengths. By means of an event-driven method, all simulations are conducted using the Leaky Integrateand-Fire with Latency (LIFL) model. Typical cases are taken into consideration, in which a network section (module) is able to process the input information, introducing a particular behavior, that we have called path multimodality. Simulation results are discussed. Through this phenomenon, the output layer of the network can generate a number of temporally spaced groups of synchronous spikes. The multimodality effect could be applied for various purposes, for instance in coding or else transmission issues

Susi, G., Cristini, A., & Salerno, M. (2016). Path multimodality in a feedforward SNN module, using LIF with latency model. NEURAL NETWORK WORLD, 26(4), 363-376 [10.14311/NNW.2016.26.021].

Path multimodality in a feedforward SNN module, using LIF with latency model

SUSI, GIANLUCA;CRISTINI, ALESSANDRO;SALERNO, MARIO
2016

Abstract

In this paper, the network transmission properties of a feedforward Spiking Neural Network (SNN) affected by synchronous stimuli are investigated with respect to the connection probability and the synaptic strengths. By means of an event-driven method, all simulations are conducted using the Leaky Integrateand-Fire with Latency (LIFL) model. Typical cases are taken into consideration, in which a network section (module) is able to process the input information, introducing a particular behavior, that we have called path multimodality. Simulation results are discussed. Through this phenomenon, the output layer of the network can generate a number of temporally spaced groups of synchronous spikes. The multimodality effect could be applied for various purposes, for instance in coding or else transmission issues
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore ING-INF/01 - Elettronica
Settore ING-IND/31 - Elettrotecnica
eng
Susi, G., Cristini, A., & Salerno, M. (2016). Path multimodality in a feedforward SNN module, using LIF with latency model. NEURAL NETWORK WORLD, 26(4), 363-376 [10.14311/NNW.2016.26.021].
Susi, G; Cristini, A; Salerno, M
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2108/189487
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