ECRAM器件如何实现低功耗边缘持续学习？这篇AICS 2025拓展摘要给你新视野。
arXiv:2607.19661v1 Announce Type: cross Abstract: Several edge computing platforms, such as autonomous vehicles and smart sensing devices, need to ada…
神经形态计算+强化学习，打造高效机器人路径规划新框架，为仓储物流自动化提速
arXiv:2606.20031v1 Announce Type: cross Abstract: Dynamic environmental changes, confined workspaces, and stringent real-time constraints make pathfin…
脉冲神经网络的局部学习规则综述与基准测试框架，助你快速理解不同训练算法的差异与适配场景
arXiv:2605.15058v1 Announce Type: cross Abstract: The rapid expansion of spiking neural networks (SNNs) has led to a proliferation of training algorit…
新型弹性脉冲 Transformer，突破静态网络限制，在神经形态硬件上高效理解手势。
arXiv:2605.13869v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs), particularly Spiking Transformers, offer energy-efficient processing…
无时钟异步电路驱动的可扩展神经形态计算架构，在FPGA上实现布尔脉冲神经元网络，突破传统时钟同步限制。
arXiv:2605.16114v1 Announce Type: cross Abstract: We propose a scalable neuromorphic architecture based on spiking dynamics emerging from the autonomo…