The switching and learning behavior of an octopus cell implemented on FPGA-Reference-Cited by-同舟云学术

The switching and learning behavior of an octopus cell implemented on FPGA

Published:2024 Issue:4 Volume:21 Page:5762-5781
ISSN:1551-0018
Container-title:Mathematical Biosciences and Engineering
language:
Short-container-title:MBE

Author:

Tschumak Alexej¹,Feldhoff Frank²,Klefenz Frank³

Affiliation:

1. Audio Communication Group, Technische Universität Berlin, Berlin, Germany

2. Advanced Electromagnetics Group, Technische Universität Ilmenau, Ilmenau, Germany

3. Fraunhofer Institute for Digital Media Technology, Ilmenau, Germany

Abstract

<abstract><p>A dendrocentric backpropagation spike timing-dependent plasticity learning rule has been derived based on temporal logic for a single octopus neuron. It receives parallel spike trains and collectively adjusts its synaptic weights in the range [0, 1] during training. After the training phase, it spikes in reaction to event signaling input patterns in sensory streams. The learning and switching behavior of the octopus cell has been implemented in field-programmable gate array (FPGA) hardware. The application in an FPGA is described and the proof of concept for its application in hardware that was obtained by feeding it with spike cochleagrams is given; also, it is verified by performing a comparison with the pre-computed standard software simulation results.</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

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