Improved memristor model with parasitic parameters

Purpose In the latest years, various innovative and hopeful applications for electronic industry are founded on memristors. They are novel, two-terminal and passive elements, having very good commutating and memory features. For design, synthesis and analysis of memristor circuits, scientists need simple, precise and fast-operating memristor models and suitable software. The purpose of this paper is to provide simplified and quickly functioning memristor models, paying attention on basic parasitic parameters – capacitance, resistance, inductance, additional small-signal DC current and voltage sources for shifting the i–v relations, and analysis of their influence on memristor operation. Models’ simplification ensures analyses of complex memristor-based devices. Design/methodology/approach The optimal values of memristor model’s coefficients and parasitic parameters are estimated, applying experimental voltage–current characteristics of Knowm memristors and using a gradient-descending technique in Simulink-MATLAB. Findings Analyses in MATLAB and LTSPICE approve the correct and fast operation of proposed memristor models, their good memory and switching properties and applicability in different electronic devices. Some potential applications of proposed models are discussed and a comparison with several widely used standard and modified models is conducted. Originality/value Simple modified models of a memristor with parasitic parameters are applied in MATLAB and LTSPICE for finding parasitic capacitance, resistance, inductance and small-signal DC voltage and current components. The amplitude response is analyzed, together with i–v relations at different frequencies in sine-wave and impulse modes.

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Publication Details

Journal
COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering
Published
2025-12-31
DOI
https://doi.org/10.1108/compel-11-2024-0491
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.73
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article

Improved memristor model with parasitic parameters

Valeri Mladenov, Stoyan Kirilov
1 citations
COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering
Advanced Memory and Neural Computing
0.73
article

Improved memristor model with parasitic parameters

Valeri Mladenov, Stoyan Kirilov
article en
1 citations

Abstract

Purpose In the latest years, various innovative and hopeful applications for electronic industry are founded on memristors. They are novel, two-terminal and passive elements, having very good commutating and memory features. For design, synthesis and analysis of memristor circuits, scientists need simple, precise and fast-operating memristor models and suitable software. The purpose of this paper is to provide simplified and quickly functioning memristor models, paying attention on basic parasitic parameters – capacitance, resistance, inductance, additional small-signal DC current and voltage sources for shifting the i–v relations, and analysis of their influence on memristor operation. Models’ simplification ensures analyses of complex memristor-based devices. Design/methodology/approach The optimal values of memristor model’s coefficients and parasitic parameters are estimated, applying experimental voltage–current characteristics of Knowm memristors and using a gradient-descending technique in Simulink-MATLAB. Findings Analyses in MATLAB and LTSPICE approve the correct and fast operation of proposed memristor models, their good memory and switching properties and applicability in different electronic devices. Some potential applications of proposed models are discussed and a comparison with several widely used standard and modified models is conducted. Originality/value Simple modified models of a memristor with parasitic parameters are applied in MATLAB and LTSPICE for finding parasitic capacitance, resistance, inductance and small-signal DC voltage and current components. The amplitude response is analyzed, together with i–v relations at different frequencies in sine-wave and impulse modes.

COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic EngineeringVol. 45(2)
Technical University of Sofia (BG)
Industry, innovation and infrastructure
Openalex Percentile: Top 20%
Advanced Memory and Neural Computing
0.73
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