Noise-Induced Homeostasis in Memristor-Based Neuromorphic Systems

E. Salvador; R. Rodriguez; E. Miranda; J. Martin-Martinez; A. Rubio; A. Crespo-Yepes; V. Ntinas; G. Ch Sirakoulis; M. Nafria

doi:10.1109/LED.2024.3416704

Noise-Induced Homeostasis in Memristor-Based Neuromorphic Systems

E. Salvador, R. Rodriguez, E. Miranda, J. Martin-Martinez, A. Rubio, A. Crespo-Yepes, V. Ntinas, G. Ch Sirakoulis, M. Nafria

Department of Electronic Engineering

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Abstract

In this work, it is experimentally demonstrated that noise can be used to emulate the biological homeostatic neuron property in memristor-based neuromorphic systems. The addition of an external noise to the bias allows regulating the memristor performance when used as an artificial neuron, controlling the firing process through the modulation of the memristor threshold voltages. Experimental results have been correctly addressed using the Dynamic Memdiode Model (DMM) for memristors in the framework of SPICE simulation

Original language	English
Pages (from-to)	1524-1527
Number of pages	4
Journal	IEEE Electron Device Letters
Volume	45
Issue number	8
DOIs	https://doi.org/10.1109/LED.2024.3416704
Publication status	Published - Aug 2024

Keywords

Memristor
RRAM
SPICE
homeostasis
resistive switching
spike neural networks
stochastic resonance

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10.1109/LED.2024.3416704

https://ddd.uab.cat/record/299290

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title = "Noise-Induced Homeostasis in Memristor-Based Neuromorphic Systems",

abstract = "In this work, it is experimentally demonstrated that noise can be used to emulate the biological homeostatic neuron property in memristor-based neuromorphic systems. The addition of an external noise to the bias allows regulating the memristor performance when used as an artificial neuron, controlling the firing process through the modulation of the memristor threshold voltages. Experimental results have been correctly addressed using the Dynamic Memdiode Model (DMM) for memristors in the framework of SPICE simulation",

keywords = "Memristor, RRAM, SPICE, homeostasis, resistive switching, spike neural networks, stochastic resonance",

author = "E. Salvador and R. Rodriguez and E. Miranda and J. Martin-Martinez and A. Rubio and A. Crespo-Yepes and V. Ntinas and Sirakoulis, {G. Ch} and M. Nafria",

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AU - Salvador, E.

AU - Rodriguez, R.

AU - Miranda, E.

AU - Martin-Martinez, J.

AU - Rubio, A.

AU - Crespo-Yepes, A.

AU - Ntinas, V.

AU - Sirakoulis, G. Ch

AU - Nafria, M.

PY - 2024/8

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N2 - In this work, it is experimentally demonstrated that noise can be used to emulate the biological homeostatic neuron property in memristor-based neuromorphic systems. The addition of an external noise to the bias allows regulating the memristor performance when used as an artificial neuron, controlling the firing process through the modulation of the memristor threshold voltages. Experimental results have been correctly addressed using the Dynamic Memdiode Model (DMM) for memristors in the framework of SPICE simulation

AB - In this work, it is experimentally demonstrated that noise can be used to emulate the biological homeostatic neuron property in memristor-based neuromorphic systems. The addition of an external noise to the bias allows regulating the memristor performance when used as an artificial neuron, controlling the firing process through the modulation of the memristor threshold voltages. Experimental results have been correctly addressed using the Dynamic Memdiode Model (DMM) for memristors in the framework of SPICE simulation

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KW - RRAM

KW - SPICE

KW - homeostasis

KW - resistive switching

KW - spike neural networks

KW - stochastic resonance

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EP - 1527

JO - IEEE Electron Device Letters

JF - IEEE Electron Device Letters

IS - 8

ER -

Noise-Induced Homeostasis in Memristor-Based Neuromorphic Systems

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