硅中AdEx神经元动力学的精确和灵活的模拟仿真
An accurate and flexible analog emulation of AdEx neuron dynamics in silicon
摘要：
模拟神经形态硬件一方面保证了快速的大脑仿真，另一方面保证了新的、受大脑启发的计算范例的有效实现。桥接这种频谱需要灵活配置的电路，其具有通过目标神经元和突触模型的准确实现而培育的可靠和可再现的动态。本文介绍了混合信号加速神经形态系统BrainScaleS-2的模拟神经元电路。他们能够灵活，准确地模拟自适应指数泄漏积分和消防模型方程结合电流和电导为基础的突触，通过精确复制广泛的复杂神经元动力学和放电模式证明。
英文摘要：
Analog neuromorphic hardware promises fast brain emulation on the one hand and an efficient implementation of novel, brain-inspired computing paradigms on the other. Bridging this spectrum requires flexibly configurable circuits with reliable and reproducible dynamics fostered by an accurate implementation of the targeted neuron and synapse models. This manuscript presents the analog neuron circuits of the mixed-signal accelerated neuromorphic system BrainScaleS-2. They are capable of flexibly and accurately emulating the adaptive exponential leaky integrate-and-fire model equations in combination with both current- and conductance-based synapses, as demonstrated by precisely replicating a wide range of complex neuronal dynamics and firing patterns.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
