Signals generated in memristive circuits
Nanoscale Systems: Mathematical Modeling, Theory and Applications (2012)
- Volume: 1, page 48-57
- ISSN: 2299-3290
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topArtur Sowa. "Signals generated in memristive circuits." Nanoscale Systems: Mathematical Modeling, Theory and Applications 1 (2012): 48-57. <http://eudml.org/doc/266711>.
@article{ArturSowa2012,
abstract = {Signals generated in circuits that include nano-structured elements typically have strongly distinct characteristics, particularly the hysteretic distortion. This is due to memristance, which is one of the key electronic properties of nanostructured materials. In this article, we consider signals generated from a memrsitive circuit model. We demonstrate numerically that such signals can be efficiently represented in certain custom-designed nonorthogonal bases. The proposed method ensures that the actual numerical representation can be implemented as a fast, O(N logN), algorithm. In addition, we discuss the possibility of modelling the hysteretic distortion via fast numerical transforms.},
author = {Artur Sowa},
journal = {Nanoscale Systems: Mathematical Modeling, Theory and Applications},
keywords = {Memristance; nanoelectronics; fast algorithms; nonlinear eigenvalue problems; memristance},
language = {eng},
pages = {48-57},
title = {Signals generated in memristive circuits},
url = {http://eudml.org/doc/266711},
volume = {1},
year = {2012},
}
TY - JOUR
AU - Artur Sowa
TI - Signals generated in memristive circuits
JO - Nanoscale Systems: Mathematical Modeling, Theory and Applications
PY - 2012
VL - 1
SP - 48
EP - 57
AB - Signals generated in circuits that include nano-structured elements typically have strongly distinct characteristics, particularly the hysteretic distortion. This is due to memristance, which is one of the key electronic properties of nanostructured materials. In this article, we consider signals generated from a memrsitive circuit model. We demonstrate numerically that such signals can be efficiently represented in certain custom-designed nonorthogonal bases. The proposed method ensures that the actual numerical representation can be implemented as a fast, O(N logN), algorithm. In addition, we discuss the possibility of modelling the hysteretic distortion via fast numerical transforms.
LA - eng
KW - Memristance; nanoelectronics; fast algorithms; nonlinear eigenvalue problems; memristance
UR - http://eudml.org/doc/266711
ER -
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