Efficient connectivity and intrinsic noise separation in recurrent spiking neural networks trained with e-prop
Biologically plausible learning rules for neural networks, such as e-prop (eligibility propagation), are essential both for advancing neuromorphic computing and for understanding fundamental mechanisms of learning in animal brains. However, their behavior under different network conditions remains u...
Kaydedildi:
| Asıl Yazarlar: | , , , |
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| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
IOP Publishing
2025-01-01
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| Seri Bilgileri: | Neuromorphic Computing and Engineering |
| Konular: | |
| Online Erişim: | https://doi.org/10.1088/2634-4386/ae0826 |
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