Publication detail

Modeling of the generic memcapacitors using higher-order multi-ports

BIOLEK, Z. BIOLKOVÁ, V. BIOLEK, D. KOLKA, Z.

Original Title

Modeling of the generic memcapacitors using higher-order multi-ports

Type

journal article in Web of Science

Language

English

Original Abstract

The paper introduces predictive modeling of generic memcapacitors using multi-port versions of fundamental elements of Chua’s table. Generic memcapacitors are the most common type of memcapacitive systems; they behave as state-dependent capacitors, with the capacitance being independent of the voltage and charge. The predictive model consists of a multiport capacitor and an associated dynamic system that represents the state of the dynamics. It is shown that the potential function of the multi-port is the energy of the electrostatic field of the memcapacitor. It enables incorporating this element into the framework of Lagrangian formalism. Practical implementations of the model are presented on specific examples from selected fields of science: a memory circuit with an electrostatically controlled bistable membrane, and a lipid bilayer model inspired by the processes that occur in cell membranes.

Keywords

Chua’s table; Multiport element; Memcapacitive system; Lagrangian

Authors

BIOLEK, Z.; BIOLKOVÁ, V.; BIOLEK, D.; KOLKA, Z.

Released

14. 5. 2022

Publisher

Elsevier

Location

Amsterodam, Holandsko

ISBN

1007-5704

Periodical

Communications in Nonlinear Science and Numerical Simulation

Year of study

113

Number

1

State

Kingdom of the Netherlands

Pages from

1

Pages to

14

Pages count

14

URL

https://www.sciencedirect.com/science/article/pii/S1007570422001423

Full text in the Digital Library

http://hdl.handle.net/11012/204312

BibTex

@article{BUT177953,
  author="Zdeněk {Biolek} and Viera {Biolková} and Dalibor {Biolek} and Zdeněk {Kolka}",
  title="Modeling of the generic memcapacitors using higher-order multi-ports",
  journal="Communications in Nonlinear Science and Numerical Simulation",
  year="2022",
  volume="113",
  number="1",
  pages="1--14",
  doi="10.1016/j.cnsns.2022.106497",
  issn="1007-5704",
  url="https://www.sciencedirect.com/science/article/pii/S1007570422001423"
}