Path multimodality in a Feedforward SNN module, using LIF with Latency model

Title:

Path multimodality in a Feedforward SNN module, using LIF with Latency model

Creator:

Susi, G., Cristini , A., and Salerno , M.

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:f1ea530a-4864-415f-96a4-222a69a73137
uuid:f1ea530a-4864-415f-96a4-222a69a73137
doi:10.14311/NNW.2016.26.021

Subject:

Feedforward SNN, LIF with latency model, Synchrony, Firing rate, and Path multimodality

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

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 Integrate-and-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.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2016 Volume:26 | Number:4

Harvested from:

CDK

Metadata only:

false