https://doi.org/10.1140/epjs/s11734-025-01994-1
Regular Article
Design of memristive afferent neuron for parallel sensing of multimodal data
Zhejiang Province Key Laboratory of Intelligent Vehicle Electronics, Hangzhou Dianzi University, 310018, Hangzhou, China
a
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Received:
1
June
2025
Accepted:
23
September
2025
Published online:
8
October
2025
Abstract
Inspired by the working mode of human brain, neurons built by memristors have great potential for efficient processing of sensing data. However, there is still a lack of a hardware circuit that can encode multiple sensing data in parallel. In this paper, we design a memristive afferent neuron that can encode pressure data and light intensity data in parallel according to the oscillating set-up time and oscillation frequency of the neuron circuit. The memristive afferent neuron is constructed using an analog circuit emulator which is consisted of multipliers, operational amplifiers, resistors, and capacitors, and the hardware system is implemented with pressure sensor and light intensity sensor. The pressure sensor realizes time-to-first-spike (TTFS) encoding of pressure data by modulating the bias resistance of the memristive neuron, whereas the light intensity sensor performs rate and temporal fusion (RTF) encoding of light intensity data by adjusting the external capacitance of the neuron. Finally, the memristive neuron is employed to perform classification experiments on liquids with varying weights and transmittance rates, which verifies its feasibility and practicability, and provides a design idea for the perception of large-scale sensing data.
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© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2025
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
