Andre Van Schaik

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Bayesian spiking neurons (BSNs) provide a probablisitic and intuitive interpretation of how spiking neurons could work and have been shown to be equivalent to leaky integrate-and-fire neurons under certain conditions [1]. The study of BSNs has been restricted mainly to small networks because online learning, which currently involves a(More)
This paper proposes a simple analogue electronic spiking neuron circuit, which can be used to create hardware models of biological neural systems. In spite of its simplicity, the circuit is able to simulate a variety of different neuron types. Measurements of the neuron model in various settings are compared with the physiological response of certain neuron(More)
Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with the no Invariant Sections, with no Front-Cover Texts, and with no Back-Cover Texts. A copy of the license is included in the section GNU Free(More)
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