Versatile CMOS Analog LIF Neuron for Memristor-Integrated Neuromorphic Circuits
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866909975019782144 |
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| author | Garg, Nikhil Florini, Davide Dufour, Patrick Muhr, Eloir Faye, Mathieu Bocquet, Marc Querlioz, Damien Beilliard, Yann Drouin, Dominique Alibart, Fabien Portal, Jean-Michel |
| author_facet | Garg, Nikhil Florini, Davide Dufour, Patrick Muhr, Eloir Faye, Mathieu Bocquet, Marc Querlioz, Damien Beilliard, Yann Drouin, Dominique Alibart, Fabien Portal, Jean-Michel |
| contents | Heterogeneous systems with analog CMOS circuits integrated with nanoscale memristive devices enable efficient deployment of neural networks on neuromorphic hardware. CMOS Neuron with low footprint can emulate slow temporal dynamics by operating with extremely low current levels. Nevertheless, the current read from the memristive synapses can be higher by several orders of magnitude, and performing impedance matching between neurons and synapses is mandatory. In this paper, we implement an analog leaky integrate and fire (LIF) neuron with a voltage regulator and current attenuator for interfacing CMOS neurons with memristive synapses. In addition, the neuron design proposes a dual leakage that could enable the implementation of local learning rules such as voltage-dependent synaptic plasticity. We also propose a connection scheme to implement adaptive LIF neurons based on two-neuron interaction. The proposed circuits can be used to interface with a variety of synaptic devices and process signals of diverse temporal dynamics. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_19667 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Versatile CMOS Analog LIF Neuron for Memristor-Integrated Neuromorphic Circuits Garg, Nikhil Florini, Davide Dufour, Patrick Muhr, Eloir Faye, Mathieu Bocquet, Marc Querlioz, Damien Beilliard, Yann Drouin, Dominique Alibart, Fabien Portal, Jean-Michel Emerging Technologies Systems and Control Heterogeneous systems with analog CMOS circuits integrated with nanoscale memristive devices enable efficient deployment of neural networks on neuromorphic hardware. CMOS Neuron with low footprint can emulate slow temporal dynamics by operating with extremely low current levels. Nevertheless, the current read from the memristive synapses can be higher by several orders of magnitude, and performing impedance matching between neurons and synapses is mandatory. In this paper, we implement an analog leaky integrate and fire (LIF) neuron with a voltage regulator and current attenuator for interfacing CMOS neurons with memristive synapses. In addition, the neuron design proposes a dual leakage that could enable the implementation of local learning rules such as voltage-dependent synaptic plasticity. We also propose a connection scheme to implement adaptive LIF neurons based on two-neuron interaction. The proposed circuits can be used to interface with a variety of synaptic devices and process signals of diverse temporal dynamics. |
| title | Versatile CMOS Analog LIF Neuron for Memristor-Integrated Neuromorphic Circuits |
| topic | Emerging Technologies Systems and Control |
| url | https://arxiv.org/abs/2406.19667 |