LEARNING
用于自适应深部脑刺激的神经形态能量感知学习
Binh Nguyen, Colleen Josephson, Mircea Teodorescu, Gert Cauwenberghs, Jason Eshraghian
- 发表年份
- 2026
- 访问权限
- 开放获取
摘要
该论文提出了一种能量感知学习方法，将执行器能耗直接纳入强化学习奖励函数，并在帕金森病深部脑刺激闭环系统中验证。通过稀疏性约束知识蒸馏将策略压缩到神经形态处理器上，实现了刺激电荷减少80%且推理功耗仅0.52毫瓦。
关键词
neuromorphic computingenergy-aware learningdeep brain stimulationreinforcement learningspiking neural network
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