Hyperdimensional Computing with Spiking-Phasor Neurons

• URL: http://arxiv.org/abs/2303.00066v1
• Date: Tue, 28 Feb 2023 20:09:12 GMT
• Title: Hyperdimensional Computing with Spiking-Phasor Neurons
• Authors: Jeff Orchard, Russell Jarvis
• Abstract summary: Symbolic Vector Architectures (VSAs) are a powerful framework for representing compositional reasoning. We run VSA algorithms on a substrate of spiking neurons that could be run efficiently on neuromorphic hardware.
• Score: 0.9594432031144714
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Vector Symbolic Architectures (VSAs) are a powerful framework for representing compositional reasoning. They lend themselves to neural-network implementations, allowing us to create neural networks that can perform cognitive functions, like spatial reasoning, arithmetic, symbol binding, and logic. But the vectors involved can be quite large, hence the alternative label Hyperdimensional (HD) computing. Advances in neuromorphic hardware hold the promise of reducing the running time and energy footprint of neural networks by orders of magnitude. In this paper, we extend some pioneering work to run VSA algorithms on a substrate of spiking neurons that could be run efficiently on neuromorphic hardware.

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