A New Compact Model for Third-order Memristive Neuron with Box-shaped Hysteresis and Dynamics Analysis

This paper proposes a new compact model and presents circuit-theoretical analysis for a third-order memristive neuromorphic element fabricated by S. Kumar et al. The proposed model mainly consists of a box-shaped resistor model and a simplified piecewise-linear memristor model. Since the dynamic beh...

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Veröffentlicht in:IEEE transactions on computer-aided design of integrated circuits and systems 2023-10, Vol.42 (10), p.1-1
Hauptverfasser: Liang, Yan, Chen, Shuaiqun, Lu, Zhenzhou, Wang, Guangyi, Iu, Herbert Ho-Ching
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Sprache:eng
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Zusammenfassung:This paper proposes a new compact model and presents circuit-theoretical analysis for a third-order memristive neuromorphic element fabricated by S. Kumar et al. The proposed model mainly consists of a box-shaped resistor model and a simplified piecewise-linear memristor model. Since the dynamic behavior of the box-shaped hysteresis in the quasi-static current-voltage curve is mostly unexplored, we firstly extract the box-shaped resistor model and construct its oscillators. The coordinate system shifting method and dynamic route analysis method are used to reveal the operating mechanism of box-shaped resistor-based oscillators. Both the theoretical analysis and simulation verification indicate that the box-shaped hysteresis characteristic facilitates the generation of neuromorphic action potentials. The proposed new compact model not only captures quasi-static characteristics, but also includes dynamic behaviors, such as action potential, periodic spiking, and periodic bursting. The influences of the model parameters are further investigated to reveal the mechanism of the neuromorphic behaviors in the box-shaped hysteresis and positive differential resistance regions. Simulation results manifest the feasibility of the proposed model and the correctness of the presented analysis methods, which pave the way to the optimized design of memristive devices and the research of neuromorphic dynamics.
ISSN:0278-0070
1937-4151
DOI:10.1109/TCAD.2023.3245543