Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Sergey V. Stasenko"'
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-11 (2023)
Abstract Coherent activations of brain neuron networks underlie many physiological functions associated with various behavioral states. These synchronous fluctuations in the electrical activity of the brain are also referred to as brain rhythms. At t
Externí odkaz:
https://doaj.org/article/20df81de11894420acdd7aa8559f5ac5
Publikováno v:
Biomimetics, Vol 8, Iss 5, p 422 (2023)
In this study, we introduce an innovative hybrid artificial neural network model incorporating astrocyte-driven short-term memory. The model combines a convolutional neural network with dynamic models of short-term synaptic plasticity and astrocytic
Externí odkaz:
https://doaj.org/article/b0e0b866289d438b915cb767d7a59f72
Publikováno v:
Mathematics, Vol 11, Iss 18, p 3888 (2023)
We consider an unstructured neuron network model composed of excitatory and inhibitory neurons. The synaptic connections are supplied with spike timing-dependent plasticity (STDP). We take the STDP model implemented using a memristor. In normal condi
Externí odkaz:
https://doaj.org/article/a92240c2a0fd480995943a4f126892f9
Publikováno v:
Biomimetics, Vol 8, Iss 3, p 277 (2023)
We propose a new model for a neuromorphic olfactory analyzer based on memristive synapses. The model comprises a layer of receptive neurons that perceive various odors and a layer of “decoder” neurons that recognize these odors. It is demonstrate
Externí odkaz:
https://doaj.org/article/8431f74b978a417c9eecfaf74695b072
Using Machine Learning Algorithms to Determine the Post-COVID State of a Person by Their Rhythmogram
Autor:
Sergey V. Stasenko, Andrey V. Kovalchuk, Evgeny V. Eremin, Olga V. Drugova, Natalya V. Zarechnova, Maria M. Tsirkova, Sergey A. Permyakov, Sergey B. Parin, Sofia A. Polevaya
Publikováno v:
Sensors, Vol 23, Iss 11, p 5272 (2023)
This study introduces a novel method for detecting the post-COVID state using ECG data. By leveraging a convolutional neural network, we identify “cardiospikes” present in the ECG data of individuals who have experienced a COVID-19 infection. Wit
Externí odkaz:
https://doaj.org/article/f523ff16d53d4e1581eaba6f6ff6ecfd
Publikováno v:
Entropy, Vol 25, Iss 5, p 745 (2023)
We investigated a mathematical model composed of a spiking neural network (SNN) interacting with astrocytes. We analysed how information content in the form of two-dimensional images can be represented by an SNN in the form of a spatiotemporal spikin
Externí odkaz:
https://doaj.org/article/dad3369ec8594f4691c5d23f50cc232e
Publikováno v:
Mathematics, Vol 11, Iss 9, p 2143 (2023)
The goal of this study is to propose a new reduced phenomenological model that describes the mean-field dynamics arising from neuron–glial interaction, taking into account short-term synaptic plasticity and recurrent connections in the presence of
Externí odkaz:
https://doaj.org/article/b2e8217669454c8e999e5121a9284eef
Publikováno v:
Mathematics, Vol 11, Iss 9, p 2109 (2023)
We propose a mathematical model of a spiking neural network (SNN) that interacts with an active extracellular field formed by the brain extracellular matrix (ECM). The SNN exhibits irregular spiking dynamics induced by a constant noise drive. Followi
Externí odkaz:
https://doaj.org/article/be4da8af542441b6a542b1974e18900b
Publikováno v:
Mathematics, Vol 11, Iss 3, p 561 (2023)
The mathematical model of the spiking neural network (SNN) supplied by astrocytes is investigated. The astrocytes are a specific type of brain cells which are not electrically excitable but induce chemical modulations of neuronal firing. We analyze h
Externí odkaz:
https://doaj.org/article/5acb25d24f4a45ed8d69920931300cc3
Autor:
Evgeny M. Mirkes, Jonathan Bac, Aziz Fouché, Sergey V. Stasenko, Andrei Zinovyev, Alexander N. Gorban
Publikováno v:
Entropy, Vol 25, Iss 1, p 33 (2022)
Domain adaptation is a popular paradigm in modern machine learning which aims at tackling the problem of divergence (or shift) between the labeled training and validation datasets (source domain) and a potentially large unlabeled dataset (target doma
Externí odkaz:
https://doaj.org/article/fc1cb24a684747288609251ceb7b827a