Yazar "Borisenok, Sergey" için listeleme
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Control of collective bursting in small Hodgkin-Haxley neuron clusters
Borisenok, Sergey; Ünal, Zeynep; Çatmabacak, Önder (Communications Faculty of Sciences University of Ankara, 2018)The speed gradient-based control algorithm for tracking the membrane potential of Hodgkin-Huxley neurons is applied to their small clusters modeling the basic features of an epileptiform dynamics. One of the neurons plays ... -
Control over performance of qubit-based sensors
Borisenok, Sergey (Institute for Problems in Mechanical Engineering, Russian Academy of Sciences, 2018)The extreme sensitivity of quantum systems towards the external perturbations and in the same time their ability to be strongly coupled to the measured target field makes them to be stable under the environmental noise. A ... -
DETECTION AND CONTROL OF EPILEPTIFORM REGIME IN THE HODGKIN–HUXLEY ARTIFICIAL NEURAL NETWORKS VIA QUANTUM ALGORITHMS
Borisenok, Sergey (Institute for Problems in Mechanical Engineering, Russian Academy of Sciences, 2022)The problem of detection and the following suppression of epileptiform dynamics in artificial neural networks (ANN) still is a hot topic in modern theoretical and applied neuroscience. For the purpose of such modeling, ... -
Energy control in a quantum oscillator using coherent control and engineered environment
Pechen, Alexander N; Borisenok, Sergey; Fradkov, Alexander L. (PERGAMON-ELSEVIER SCIENCE, 2022)We develop and analyze a new method for manipulation of energy in a quantum harmonic oscillator using coherent, e.g., electromagnetic, field and incoherent control. Coherent control is typically implemented by shaped laser ... -
Ergotropy of bosonic quantum battery driven via repelling feedback algorithms
Borisenok, Sergey; Gürsey, Feza (Institute for Problems in Mechanical Engineering, Russian Academy of Sciences, 2021)Feedback algorithms can be efficiently applied to control the basic characteristics of quantum batteries (QBs): the ergotropy, the charging power, the storage capacity and others. We invent here two alternative approaches, ... -
Hodgkin-Huxley Nöronlarında Ani Yükseliş ve Fırlama Dinamiklerinin Kontrolü
Borisenok, Sergey (TUBİTAK, 2018)Ani yükselen nöronları içeren ağlar, pek çok örüntü tanıma ve hesaplamalı nörobilim uygulamalarında önemli bir rol oynamaktadır. Modern deneysel bilim, biyolojik nöronların dinamiklerinin manipülasyonunda büyük bir ... -
Parameter investigation of topological data analysis for EEG signals
Altindis, Fatih; Yilmaz, Bulent; Borisenok, Sergey; Icoz, Kutay (ELSEVIER SCI LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND, 01.01.2021)Topological data analysis (TDA) methods have become appealing in EEG signal processing, because they may help the scientists explore new features of complex and large amount of data by simplifying the process from a ... -
Target attractor formed via fractional feedback control
Borisenok, Sergey (YILDIZ TECHNICAL UNIVYILDIZ CAMPUS, BESIKTAS, ISTANBUL 34349, TURKEY, 2021)We discuss here the stabilization problem for an ordinary differential equation (ODE) dynamical model. To make such a control, one can form a Kolesnikov’s subset attracting the phase trajectories to its neighborhood in the ... -
Target Attractor Tracking of Relative Phase in Bosonic Josephson Junction
Borisenok, Sergey (AMER INST PHYSICS2 HUNTINGTON QUADRANGLE, STE 1NO1, MELVILLE, NY 11747-4501 USA, 2016)The relative phase of Bosonic Josephson junction in the Josephson regime of Bose-Hubbard model is tracked via the target attractor ('synergetic') feedback algorithm with the inter-well coupling parameter presented as a ... -
Use of Topological Data Analysis in Motor Intention Based Brain-Computer Interfaces
Altindis, Fatih; Yilmaz, Bulent; Borisenok, Sergey; Icoz, Kutay (IEEE COMPUTER SOC, 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA, 2018)This study aims to investigate the use of topological data analysis in electroencephalography (EEG) based on brain computer interface (BC!) applications. Our study focused on extracting topological features of EEG signals ...
