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2020 | OriginalPaper | Chapter

Axonal Delay Controller for Spiking Neural Networks Based on FPGA

Authors : Mireya Zapata, Jordi Madrenas, Miroslava Zapata, Jorge Alvarez

Published in: Advances in Artificial Intelligence, Software and Systems Engineering

Publisher: Springer International Publishing

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Abstract

In this paper, the implementation of a programmable Axonal Delay Controller (ADyC) mapped on a hardware Neural Processor (NP) FPGA-based is reported. It is possible to define axonal delays between 1 to 31 emulation cycles to global and local pre-synaptic spikes generated by NP, extending the temporal characteristics supported by this architecture. The prototype presented in this work contributes to the realism of the network, which mimics the temporal biological characteristics of spike propagation through the cortex. The contribution of temporal information is strongly related to the learning process. ADyC operation is transparent for the rest of the system and neither affects the remaining tasks executed by the NP nor the emulation time period. In addition, an example implemented on hardware of a neural oscillator with programmable delays configured for a set of neurons is presented in order to demonstrate full platform functionality and operability.

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Title: Axonal Delay Controller for Spiking Neural Networks Based on FPGA
Authors: Mireya Zapata
Jordi Madrenas
Miroslava Zapata
Jorge Alvarez
Publisher: Springer International Publishing
Book: Advances in Artificial Intelligence, Software and Systems Engineering
Print ISBN: 978-3-030-20453-2

Electronic ISBN: 978-3-030-20454-9

Copyright Year: 2020
DOI: https://doi.org/10.1007/978-3-030-20454-9_29

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