Evidence map›Paper›PMID 40731678›Full record

ArticleMicromachines2025

Tunable Active Wien Filters Based on Memristors.

Elena Solovyeva, Artyom Serdyuk, Yury Inshakov

Abstract read
In one paragraph

Article in Micromachines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Elena SolovyevaDepartment of Electrical Engineering Theory, Saint Petersburg Electrotechnical University "LETI", 197022 St. Petersburg, Russia.ORCID 0000-0001-8204-6632
Artyom SerdyukDepartment of Electrical Engineering Theory, Saint Petersburg Electrotechnical University "LETI", 197022 St. Petersburg, Russia.
Yury InshakovDepartment of Electrical Engineering Theory, Saint Petersburg Electrotechnical University "LETI", 197022 St. Petersburg, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Devices with tunable characteristics and parameters are used in many technical fields. Such devices can be based on memristors, which serve as programmable potentiometers. The quality of the tuning is higher by means of memristors than with mechanical and digital potentiometers. We investigate a bandpass filter in the form of an active Wien bridge with a memristor. The filter is analyzed with the help of the nodal voltage method. The dependence of the resonance frequency on the parameters of the Wien circuit, the dependence of the quality factor, and the filter gain at resonant frequency on the parameters of the voltage divider are obtained. The dependences of the resonant frequency, quality factor, and gain at the resonant frequency on the parameters of the Wien filter were formed. The tuning of the main frequency features (the filter gain, quality factor, and resonance frequency) is shown to be independent. Under different values of memristance, the frequency features result from a simulation in LTspice. These features are less than 1 percent different from the corresponding features obtained analytically. Thus, the high precision of modeling and tuning of the frequency characteristics of the memristive Wien filter is demonstrated.

Indexed as

filterLTspicememristive devicememristormodelingtunable characteristic

Identifiers

PMID40731678
PMCPMC12297913

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.