Analysis of synaptic weight distribution in an Izhikevich network

Guo, Li, Yang, Zhijun 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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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)
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: 03 Apr 2019 03:46
URI: https://eprints.mdx.ac.uk/id/eprint/9962

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