Analysis of synaptic weight distribution in an Izhikevich network
Guo, Li, Yang, Zhijun ORCID: https://orcid.org/0000-0003-2615-4297 and Zhu, Qingbao
(2013)
Analysis of synaptic weight distribution in an Izhikevich network.
In: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, 24-26 Apr 2013, Bruges, Belgium.
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[Conference or Workshop Item]
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Abstract
Izhikevich network is a relatively new neuronal network, which consists of cortical spiking model neurons with axonal conduction delays and spike-timingdependent
plasticity (STDP) with hard bound adaptation. In this work, we use uniform and Gaussian distributions respectively to initialize the weights of all excitatory neurons. After the network undergoes a few minutes of STDP adaptation, we can see that the weights of all synapses in the network, for both initial weight distributions, form a bimodal distribution, and numerically the established distribution presents dynamic stability.
Item Type: | Conference or Workshop Item (Paper) |
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Research Areas: | A. > School of Science and Technology > Design Engineering and Mathematics |
Item ID: | 9962 |
Useful Links: | |
Depositing User: | Zhijun Yang |
Date Deposited: | 28 Feb 2013 06:34 |
Last Modified: | 09 Feb 2022 10:15 |
URI: | https://eprints.mdx.ac.uk/id/eprint/9962 |
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