| Jahr | 2025 |
| Autor(en) | Robin Dietrich, Philipp Spilger, Eric Müller, Johannes Schemmel, Alois C. Knoll |
| Titel | Sequence Learning with Analog Neuromorphic Multi-Compartment Neurons and On-Chip Structural STDP |
| KIP-Nummer | HD-KIP 25-112 |
| KIP-Gruppe(n) | F9 |
| Dokumentart | Paper |
| doi | 10.1007/978-3-031-82487-6_15 |
| Abstract (en) | Neuromorphic computing is a candidate for advancing today's AI systems towards fast and efficient online learning and inference. By exploiting biological principles, mixed-signal neuromorphic chips are well suited for emulating spiking neural networks (SNNs). Nevertheless, especially time-coded SNNs tend to struggle with the noise, uncertainty, and heterogeneity introduced by analog neuromorphic. |
| bibtex | @inproceedings{dietrich2025sequence,
author = {Dietrich, Robin and Spilger, Philipp and M{\"u}ller, Eric and Schemmel, Johannes and Knoll, Alois C.},
title = {Sequence Learning with Analog Neuromorphic Multi-Compartment Neurons and On-Chip Structural STDP},
booktitle = {},
year = {2025},
pages = {207--230}
} |
