Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Fedor Pavlovich Meshchaninov"'
Autor:
Dmitry Alexeevich Zhevnenko, Fedor Pavlovich Meshchaninov, Vladislav Sergeevich Kozhevnikov, Evgeniy Sergeevich Shamin, Oleg Alexandrovich Telminov, Evgeniy Sergeevich Gornev
Publikováno v:
Micromachines, Vol 12, Iss 10, p 1220 (2021)
Memristors are among the most promising devices for building neural processors and non-volatile memory. One circuit design stage involves modeling, which includes the option of memristor models. The most common approach is the use of compact models,
Externí odkaz:
https://doaj.org/article/512e725fbdd74814aae9fef01080bc7f
Autor:
Fedor Pavlovich Meshchaninov, Dmitry Alexeevich Zhevnenko, Vladislav Sergeevich Kozhevnikov, Evgeniy Sergeevich Shamin, Oleg Alexandrovich Telminov, Evgeniy Sergeevich Gornev
Publikováno v:
Micromachines, Vol 12, Iss 10, p 1201 (2021)
The use of low-dimensional materials is a promising approach to improve the key characteristics of memristors. The development process includes modeling, but the question of the most common compact model applicability to the modeling of device charac
Externí odkaz:
https://doaj.org/article/602a9b28c9ff408199ca7ffcf5ce9fc3
Autor:
Evgeniy Shamin, Fedor Pavlovich Meshchaninov, Vladislav Kozhevnikov, Oleg Alexandrovich Telminov, Evgeniy Gornev, Dmitry Alexeevich Zhevnenko
Publikováno v:
Micromachines; Volume 12; Issue 10; Pages: 1220
Micromachines, Vol 12, Iss 1220, p 1220 (2021)
Micromachines
Micromachines, Vol 12, Iss 1220, p 1220 (2021)
Micromachines
Memristors are among the most promising devices for building neural processors and non-volatile memory. One circuit design stage involves modeling, which includes the option of memristor models. The most common approach is the use of compact models,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5116f729ba00193253831e3a4de38f86
Autor:
Evgeniy Gornev, Evgeniy Shamin, Fedor Pavlovich Meshchaninov, Dmitriy Zhevnenko, Vladislav Kozhevnikov
Publikováno v:
Mathematical modeling in materials science of electronic component.
The focus of this work is on the algorithm of extraction of parameters of the memristor model from the experimentally obtained current-voltage characteristics. The problem of finding the initial guess for this algorithm based on current-voltage chara
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f838356a2a75fefa19ecee5c3c5074bc
https://doi.org/10.29003/m1539.mmmsec-2020/127-130
https://doi.org/10.29003/m1539.mmmsec-2020/127-130
Autor:
Vladislav Kozhevnikov, Evgeniy Shamin, Fedor Pavlovich Meshchaninov, Dmitriy Zhevnenko, Evgeniy Gornev
Publikováno v:
International Forum “Microelectronics – 2020”. Joung Scientists Scholarship “Microelectronics – 2020”. XIII International conference «Silicon – 2020». XII young scientists scholarship for silicon nanostructures and devices physics, material science, process and analysis.
This work is dedicated to the development of algorithms for prediction of memristor model parameters via features of its current-voltage characteristic with the help of machine learning. An algorithm for extraction of current-voltage characteristic f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8483e13c8ae0732aae08400dfa14a8c6
https://doi.org/10.29003/m1640.silicon-2020/328-331
https://doi.org/10.29003/m1640.silicon-2020/328-331
Autor:
S. A. Gerasimova, Alexey Belov, Vladislav Kozhevnikov, Davud V. Guseinov, Evgeniy Shamin, Fedor Pavlovich Meshchaninov, Dmitry Alexeevich Zhevnenko, Alexey Mikhaylov, Evgeniy Gornev
Publikováno v:
Chaos, Solitons & Fractals. 142:110382
Memristor based device development is among the most promising and fast developing branches of modern microelectronics. Therefore, memristor modeling remains an important task due to constant improvement in understanding of resistive switching mechan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4db8c1e0d7dec4011b3eed82fd433090
https://doi.org/10.1016/j.chaos.2020.110382
https://doi.org/10.1016/j.chaos.2020.110382