Spike-TCN with Depthwise-Separable Convolution and Attention for Efficient Time Series Prediction
Abstract Spiking Neural Networks, known for their event-driven and energy-efficient characteristics, offer promising potential in temporal modeling. However, existing SNN-based models often struggle to capture long-range dependencies and inter-channel interactions, limiting their performance in comp...
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| Hlavní autoři: | , , , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Springer
2025-11-01
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| Edice: | International Journal of Computational Intelligence Systems |
| Témata: | |
| On-line přístup: | https://doi.org/10.1007/s44196-025-01063-4 |
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