The simulation problem of very large fully asynchronous Spiking Neural Networks is considered in this paper. To this purpose, a preliminary accurate analysis of the latency time is made, applying classical modelling methods to single neurons. The latency characterization is then used to propose a simplified model, able to simulate large neural networks. On this basis, networks, with up to 100,000 neurons for more than 100,000 spikes, can be simulated in a quite short time with a simple MATLAB program. Plasticity algorithms are also applied to emulate interesting global effects as the Neuronal Group Selection.
Salerno, M., Susi, G., Cristini, A. (2011). Accurate latency characterization for very large asynchronous spiking neural networks. In BIOINFORMATICS 2011 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms (pp.116-124). Lisbona -- PRT : SciTePress [10.5220/0003134601160124].
Accurate latency characterization for very large asynchronous spiking neural networks
SALERNO, MARIO;SUSI, GIANLUCA;
2011-01-01
Abstract
The simulation problem of very large fully asynchronous Spiking Neural Networks is considered in this paper. To this purpose, a preliminary accurate analysis of the latency time is made, applying classical modelling methods to single neurons. The latency characterization is then used to propose a simplified model, able to simulate large neural networks. On this basis, networks, with up to 100,000 neurons for more than 100,000 spikes, can be simulated in a quite short time with a simple MATLAB program. Plasticity algorithms are also applied to emulate interesting global effects as the Neuronal Group Selection.| File | Dimensione | Formato | |
|---|---|---|---|
|
ACCURATE LATENCY CHARACTERIZATION FOR VERY LARGE ASYNCHRONOUS SPIKING NEURAL NETWORKS(2).pdf
accesso aperto
Dimensione
304.54 kB
Formato
Adobe PDF
|
304.54 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
