no code implementations • 28 Aug 2023 • Maksim Belyaev, Murugappan Murugappan, Andrei Velichko, Dmitry Korzun
We computed different types of entropy from EEG signals and found that Fuzzy Entropy performed the best in diagnosing and monitoring PD using rs-EEG.
no code implementations • 14 Jun 2023 • Irewola Aaron Oludehinwa, Andrei Velichko, Maksim Belyaev, Olasunkanmi I. Olusola
In this study, we developed a technique of tracking the sun's activity using 2D circular kernel time series transformation, statistical and entropy measures, with machine learning approaches.
no code implementations • 3 Jun 2023 • Andrei Velichko, Petr Boriskov, Maksim Belyaev, Vadim Putrolaynen
The study presents a bio-inspired chaos sensor model based on the perceptron neural network for the estimation of entropy of spike train in neurodynamic systems.
1 code implementation • 31 Mar 2023 • Andrei Velichko, Maksim Belyaev, Yuriy Izotov, Murugappan Murugappan, Hanif Heidari
Entropy measures are effective features for time series classification problems.
no code implementations • 22 Oct 2022 • Mehmet Tahir Huyut, Andrei Velichko, Maksim Belyaev
Furthermore, in the HGB model operated with a single feature, the most efficient features were procalcitonin (F1^2 = 0. 96) and ferritin (F1^2 = 0. 91).
no code implementations • 13 Oct 2022 • Andrei Velichko, Maksim Belyaev, Matthias P. Wagner, Alireza Taravat
The results of entropy approximation are demonstrated using the example of calculating the 2D entropy of Sentinel-2 images and R^2 metric evaluation.
no code implementations • 8 Sep 2022 • Andrei Velichko, Mehmet Tahir Huyut, Maksim Belyaev, Yuriy Izotov, Dmitry Korzun
In particular, machine learning (ML) sensors for the prompt diagnosis of COVID-19 are an important option for IoT application in healthcare and ambient assisted living (AAL).
no code implementations • 20 May 2022 • Mehmet Tahir Huyut, Andrei Velichko
Since February 2020, the world has been engaged in an intense struggle with the COVID-19 dis-ease, and health systems have come under tragic pressure as the disease turned into a pandemic.
no code implementations • 25 Feb 2022 • Hanif Heidari, Andrei Velichko, Murugappan Murugappan, Muhammad E. H. Chowdhury
Firstly, this work investigates different methods of filling the reservoir with time series (signal) elements.
no code implementations • 5 Aug 2021 • Andrei Velichko
The method effectively solves classification problems and calculates risk factors for the presence of a disease in a patient according to a set of medical health indicators.
no code implementations • 18 Jul 2021 • Andrei Velichko, Hanif Heidari
Greater complexity in the time series leads to a higher classification accuracy and higher NNetEn values.
no code implementations • 30 May 2021 • Hanif Heidari, Andrei Velichko
In the age of neural networks and Internet of Things (IoT), the search for new neural network architectures capable of operating on devices with limited computing power and small memory size is becoming an urgent agenda.
no code implementations • 4 Jun 2020 • Andrei Velichko
This study presents a neural network which uses filters based on logistic mapping (LogNNet).
no code implementations • 7 Jan 2020 • Alexander Pergament, Andrei Velichko, Maksim Belyaev, Vadim Putrolaynen
With a decrease in dimensions, a decrease in the thermal coupling action radius is observed, which can vary in the range from 0. 5 to 50 {\mu}m for structures with characteristic dimensions of 0. 1 to 5 {\mu}m, respectively.
Applied Physics Disordered Systems and Neural Networks
no code implementations • 7 Jan 2020 • Andrei Velichko, Maksim Belyaev, Vadim Putrolaynen, Alexander Pergament, Valentin Perminov
In the present paper, we report on the switching dynamics of both single and coupled VO2-based oscillators, with resistive and capacitive coupling, and explore the capability of their application in oscillatory neural networks.
no code implementations • 6 Jan 2020 • Andrei Velichko, Maksim Belyaev, Vadim Putrolaynen, Valentin Perminov, Alexander Pergament
In the case of a "weak" coupling, synchronization is accompanied by attraction effect and decrease of the main spectra harmonics width.
no code implementations • 23 Nov 2019 • Andrei Velichko, Petr Boriskov
The study presents an oscillator circuit for a spike neural network with the possibility of firing rate coding and sigmoid-like activation function.
no code implementations • 6 Jun 2019 • Andrei Velichko
The family of metrics is proposed to create a neural network information converter based on a network of pulsed oscillators.
no code implementations • 10 Apr 2018 • Andrei Velichko, Vadim Putrolaynen, Maksim Belyaev
In the circuit of two thermally coupled VO2 oscillators, we studied a higher order synchronization effect, which can be used in object classification techniques to increase the number of possible synchronous states of the oscillator system.