Macromodeling of the memristor using piecewise volterra series

Ma, Chao; Xie, Shengli; Jia, Yingmin; Lin, Guan‐Yu

doi:10.1016/j.mejo.2013.11.017

Cited by 10 publications

(4 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Here the piecewise linear technique is applied to achieve it. Piecewise and piecewise linear techniques have long been used to model and analyze nonlinear electronic circuit [13], including the memristor [14], [15], [16]. For example, piecewise linear flux-charge relationship was proposed in [14].…”

Section: Flux-voltage Controlled Memristor Modelmentioning

confidence: 99%

Modeling the AgInSbTe Memristor

Miao

Wang

et al. 2015

RADIOENGINEERING

View full text Add to dashboard Cite

The AgInSbTe memristor shows gradual resistance tuning characteristics, which makes it a potential candidate to emulate biological plastic synapses. The working mechanism of the device is complex, and both intrinsic charge-trapping mechanism and extrinsic electrochemical metallization effect are confirmed in the AgInSbTe memristor. Mathematical model of the AgInSbTe memristor has not been given before. We propose the flux-voltage controlled memristor model. With piecewise linear approximation technique, we deliver the flux-voltage controlled memristor model of the AgInSbTe memristor based on the experiment data. Our model fits the data well. The flux-voltage controlled memristor model and the piecewise linear approximation method are also suitable for modeling other kinds of memristor devices based on experiment data.

show abstract

Section: Flux-voltage Controlled Memristor Modelmentioning

confidence: 99%

Modeling the AgInSbTe Memristor

Miao

Wang

et al. 2015

RADIOENGINEERING

View full text Add to dashboard Cite

show abstract

“…The "black box" (behavioral) models are universal. Within the framework of the "black box" principle, behavioral modeling of the object, which is presented as a "black or gray box", establishes the unique input-output correspondence between the sets of the input and output signals [34][35][36][37]. Universal behavioral models include the following:…”

Section: Introductionmentioning

confidence: 99%

“…The “black box” (behavioral) models are universal. Within the framework of the “black box” principle, behavioral modeling of the object, which is presented as a “black or gray box”, establishes the unique input–output correspondence between the sets of the input and output signals [ 34 , 35 , 36 , 37 ]. Universal behavioral models include the following: The functional Volterra series in time and frequency forms [ 37 , 38 , 39 , 40 , 41 ]; Regression models, mostly recurrent [ 37 ]; Models based on split signals [ 42 , 43 ].…”

Section: Introductionmentioning

confidence: 99%

Behavioral Modeling of Memristors under Harmonic Excitation

Solovyeva,

Serdyuk

2023

Micromachines

View full text Add to dashboard Cite

Memristors are devices built on the basis of fourth passive electrical elements in nanosystems. Because of the multitude of technologies used for memristor implementation, it is not always possible to obtain analytical models of memristors. This difficulty can be overcome using behavioral modeling, which is when mathematical models are constructed according to the input–output relationships on the input and output signals. For memristor modeling, piecewise neural and polynomial models with split signals are proposed. At harmonic input signals of memristors, this study suggests that split signals should be formed using a delay line. This method produces the minimum number of split signals and, as a result, simplifies behavioral models. Simplicity helps reduce the dimension of the nonlinear approximation problem solved in behavioral modeling. Based on the proposed method, the piecewise neural and polynomial models with harmonic input signals were constructed to approximate the transfer characteristic of the memristor, in which the current dynamics are described using the Bernoulli differential equation. It is shown that the piecewise neural model based on the feedforward network ensures higher modeling accuracy at almost the same complexity as the piecewise polynomial model.

show abstract

“…Many scholars have made great contributions in this regard. The piecewise Volterra series macromodeling method was proposed for the memristor [11]. This approach that combines the piecewise idea with the Volterra series method aims at significantly reducing the complexity of the traditional Volterra series model.…”

Section: Introductionmentioning

confidence: 99%

Complex Frequency Domain Analysis of Memristor Based on Volterra Series

WANG¹,

JIA²

2022

IEICE Trans. Fundamentals

View full text Add to dashboard Cite

At present, the application of different types of memristors in electronics is being deeply studied. Given the nonlinearity characterizing memristors, a circuit with memristors cannot be treated by classical circuit analysis. In this paper, memristor is equivalent to a nonlinear dynamic system composed of linear dynamic system and nonlinear static system by Volterra series. The nonlinear transfer function of memristor is derived. In the complex frequency domain, the n-order complex frequency response of memristor is established by multiple Laplace transform, and the response of MLC parallel circuit is taken as an example to verify. Theoretical analysis shows that the complex frequency domain analysis method of memristor transforms the problem of solving nonlinear circuit in time domain into n times complex frequency domain analysis of linear circuit, which provides an idea for nonlinear dynamic system analysis.

show abstract

Macromodeling of the memristor using piecewise volterra series

Cited by 10 publications

References 22 publications

Modeling the AgInSbTe Memristor

Modeling the AgInSbTe Memristor

Behavioral Modeling of Memristors under Harmonic Excitation

Complex Frequency Domain Analysis of Memristor Based on Volterra Series

Contact Info

Product

Resources

About