Журнал - CYBERNETICS AND PHYSICS / 2024 год / Выпуск № 4 — Институт Проблем Машиноведения РАН ( ИПМаш РАН )

Control over the training performance of quantum state tomography with reservoir computing networks

Авторы:

Sergey Borisenok

Страницы:

275–280

ДОИ (doi):

https://doi.org/10.35470/2226-4116-2024-13-4-275-280

On cycle slipping in infinite-dimensional control systems with periodic nonlinearities

Авторы:

Alexandr P. Elsakov , Anton Proskurnikov , Vera Smirnova

Страницы:

281–287

ДОИ (doi):

https://doi.org/10.35470/2226-4116-2024-13-4-281-287

New algorithms for restoring DNA matrix and their statistical study

Авторы:

Boris Melnikov

Страницы:

288–295

ДОИ (doi):

https://doi.org/10.35470/2226-4116-2024-13-4-288-295

Identification of neural mass network parameters using EEG evoked potential data

Авторы:

к.ф.м.н. Плотников С.А.

Страницы:

296–301

ДОИ (doi):

https://doi.org/10.35470/2226-4116-2024-13-4-296-301

Quantum probabilistic space analysis for enhanced two-wheeler traffic safety: from classical limitations toadvanced quantum circuits

Авторы:

Natarajan Shriethar

Страницы:

302–322

ДОИ (doi):

https://doi.org/10.35470/2226-4116-2024-13-4-302-322

NIRsViT: a novel deep learning model for manure identification using near-infrared-spectroscopy and imbalanced data handling

Авторы:

Nguyen Van Hieu , Ngo Le Huy Hien , Minh Toan Dinh , Phan Binh , Minh Nhat Phan , Phung Thi Anh , Le Viet Hung , Nguyen Huy Tuong

Страницы:

323–333

ДОИ (doi):

https://doi.org/10.35470/2226-4116-2024-13-4-323-333

Neural networks with iterative parameter generation for determining parameters of constitutive models

Авторы:

Yuyi Zhang , Shixiang Zhao , к.ф.м.н. Казаринов Н.А. , д.ф.м.н. Петров Ю.В.

Страницы:

334–345

ДОИ (doi):

https://doi.org/10.35470/2226-4116-2024-13-4-334-345

МИНОБРНАУКИ РОССИИ
Федеральное государственное бюджетное учреждение науки
Институт проблем машиноведения Российской академии наук

Выпуск № 4

Control over the training performance of quantum state tomography with reservoir computing networks

On cycle slipping in infinite-dimensional control systems with periodic nonlinearities

New algorithms for restoring DNA matrix and their statistical study

Identification of neural mass network parameters using EEG evoked potential data

Quantum probabilistic space analysis for enhanced two-wheeler traffic safety: from classical limitations toadvanced quantum circuits

NIRsViT: a novel deep learning model for manure identification using near-infrared-spectroscopy and imbalanced data handling

Neural networks with iterative parameter generation for determining parameters of constitutive models

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