Spiking neural network equalization on neuromorphic hardware for IM/DD optical communication
A spiking neural network (SNN) non-linear equalizer model is implemented on the mixed-signal neuromorphic hardware system BrainScaleS-2 and evaluated for an IM/DD link. The BER 2e-3 is achieved with a hardware penalty less than 1 dB, outperforming numeric linear equalization.
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| Main Authors: | , , , , , , |
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| Format: | Article (Journal) Chapter/Article |
| Language: | English |
| Published: |
2022-05-11
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| In: |
Arxiv
Year: 2022, Pages: 1-6 |
| DOI: | 10.48550/arXiv.2206.00401 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.48550/arXiv.2206.00401 Verlag, lizenzpflichtig, Volltext: http://arxiv.org/abs/2206.00401 |
| Author Notes: | Elias Arnold, Georg Böcherer, Eric Müller, Philipp Spilger, Johannes Schemmel, Stefano Calabrò, Maxim Kuschnerov |
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| 520 | |a A spiking neural network (SNN) non-linear equalizer model is implemented on the mixed-signal neuromorphic hardware system BrainScaleS-2 and evaluated for an IM/DD link. The BER 2e-3 is achieved with a hardware penalty less than 1 dB, outperforming numeric linear equalization. | ||
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