Biologically Plausible Ferroelectric Quasi-Leaky Integrate and Fire Neuron

2019 Symposium on VLSI Technology(2019)

引用 22|浏览6
暂无评分
摘要
Biologically plausible mechanism like homeostasis compliments Hebbian learning to allow unsupervised learning in spiking neural networks [1]. In this work, we propose a novel ferroelectric-based quasi-LIF neuron that induces intrinsic homeostasis. We experimentally characterize and perform phase-field simulations to delineate the non-trivial transient polarization relaxation mechanism associated with multi-domain interaction in poly-crystalline ferroelectric, such as Zr doped HfO 2 , that underlines the Q-LIF behavior. Network level simulations with the Q-LIF neuron model exhibits a 2.3x reduction in firing rate compared to traditional LIF neuron while maintaining iso-accuracy of 84-85% across varying network sizes. Such an energy-efficient hardware for spiking neuron can enable ultra-low power data processing in energy constrained environments suitable for edge-intelligence.
更多
查看译文
关键词
unsupervised learning,neural networks,intrinsic homeostasis,phase-field simulations,nontrivial transient polarization relaxation mechanism,multidomain interaction,poly-crystalline ferroelectric,Q-LIF behavior,network level simulations,Q-LIF neuron model,spiking neuron,biologically plausible ferroelectric quasileaky integrate,plausible mechanism,homeostasis compliments Hebbian learning,ferroelectric-based quasi-LIF neuron,energy-efficient hardware
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要