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Importance of the Window Function Choice for the Predictive Modelling of Memristors
- Source :
- IEEE Transactions on Circuits and Systems Ii-Express Briefs. 68(6):2167-2171
- Publication Year :
- 2021
-
Abstract
- Window functions are widely employed in memristor models to restrict the changes of the internal state variables to specified intervals. Here, we show that the actual choice of window function is of significant importance for the predictive modelling of memristors. Using a recently formulated theory of memristor attractors, we demonstrate that whether stable fixed points exist depends on the type of window function used in the model. Our main findings are formulated in terms of two memristor attractor theorems, which apply to broad classes of memristor models. As an example of our findings, we predict the existence of stable fixed points in Biolek window function memristors and their absence in memristors described by the Joglekar window function, when such memristors are driven by periodic alternating polarity pulses. It is anticipated that the results of this brief will contribute toward the development of more sophisticated models of memristive devices and systems.
- Subjects :
- State variable
Computer science
02 engineering and technology
Memristor
Type (model theory)
Fixed point
Topology
Window function
law.invention
Predictive models
Computer Science::Hardware Architecture
Computer Science::Emerging Technologies
Mathematical model
law
Attractor
0202 electrical engineering, electronic engineering, information engineering
Evolution (biology)
Electrical and Electronic Engineering
Polarity (mutual inductance)
threshold voltage
020208 electrical & electronic engineering
memristive systems
Biological system modeling
020206 networking & telecommunications
memristors
Integrated circuit modeling
Predictive modelling
Subjects
Details
- Language :
- English
- ISSN :
- 15497747
- Volume :
- 68
- Issue :
- 6
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Circuits and Systems Ii-Express Briefs
- Accession number :
- edsair.doi.dedup.....00027fee24df34ac9b48fa441dcb7ce3