CMOS Implementation of Spiking Equilibrium Propagation for Real-Time Learning.
2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS)(2022)
摘要
Equilibrium propagation (EqProp) and its adaptations for spiking neural networks (SNN) are presented as biologically plausible alternatives to back-propagation (BP) which describe a potential low-energy means of learning complex tasks in neuromorphic hardware. These algorithms are conducive to extremely efficient analog computing approaches, but a detailed analog circuit implementation and architectural outline have not yet been presented. Furthermore, current theoretical analog designs of EqProp have not addressed synapse circuit-level implementations capable of simultaneous sensing and weight updates for real-time learning. To this end, we have designed and simulated a circuit-level implementation of a spiking EqProp neuron and synapse in CMOS 65 nm technology capable of concurrent inference and weight updates for real-time learning.
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关键词
neuromorphic,CMOS,equilibrium propagation
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