Delay Learning in a Biologically Plausible Reservoir Computing Model
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2013-08-22
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en
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Abstract
In this thesis, a reservoir model created by Paugam-Moisy et al. (2008) was replicated,
and subsequently modified to be more biologically plausible. The use of a di erent
neuron model and STDP function had no negative impact on performance. For the delay
learning mechanism, replacing delay adaptation with delay selection proved viable, but
did result in somewhat lower performance. It was discovered here that the reservoir
in this model served no purpose. Therefore, the use of a small-world Watts-Strogatz
reservoir instead of a randomly connected reservoir, could not affect performance.
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Faculteit der Sociale Wetenschappen