Simulation of memristive crossbar arrays for seizure detection and prediction using parallel Convolutional Neural Networks [Formula presented]

Journal Publication ResearchOnline@JCU
Li, Chenqi;Lammie, Corey;Amirsoleimani, Amirali;Rahimi Azghadi, Mostafa;Genov, Roman
Mostafa Rahimi Azghadi
Abstract

For epileptic seizure detection and prediction, to address the computational bottleneck of the von Neumann architecture, we develop an in-memory memristive crossbar-based accelerator simulator. The simulator software is composed of a Python-based neural network training component and a MATLAB-based memristive crossbar array component. The software provides a baseline network for developing deep learning-based signal processing tasks, as well as a platform to investigate the impact of weight mapping schemes and device and peripheral circuitry non-idealities.

Journal

Software Impacts

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Volume

15

ISBN/ISSN

2665-9638

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Issue

March

Pages Count

4

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Publisher

Elsevier

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Publisher Location

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Url

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Date

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EISSN

N/A

DOI

10.1016/j.simpa.2023.100473