Effects of Higher Order and Long-Range Synchronizations for Classification and Computing in Oscillator-Based Spiking Neural Networks. - Andrey Velichko; Vadim Putrolaynen; Maksim Belyaev (CoRR, 2018)

Model of an oscillatory neural network with multilevel neurons for pattern recognition. - Andrey Velichko; Maksim Belyaev; Petr Boriskov (CoRR, 2018)

The non-capacitor model of leaky integrate-and-fire VO2 neuron with the thermal mechanism of the membrane potential. - Andrey Velichko; Maksim Belyaev; D. V. Ryabokon; S. D. Khanin (CoRR, 2019)

Capacitorless Model of a VO2 Oscillator. - Maksim Belyaev; A. A. Velichko (CoRR, 2019)

FPGA-based testing system of NAND-memory multi-chip modules. - Sergey Podryadchikov; Vadim Putrolaynen; Maksim Belyaev; Mikhail Chuvstvin; Igor Tabachnik (Microelectron. J., 2019)

Thermal coupling and effect of subharmonic synchronization in a system of two VO2 based oscillators. - Andrei Velichko; Maksim Belyaev; Vadim Putrolaynen; Valentin Perminov; Alexander Pergament (CoRR, 2020)

Switching dynamics of single and coupled VO2-based oscillators as elements of neural networks. - Andrei Velichko; Maksim Belyaev; Vadim Putrolaynen; Alexander Pergament; Valentin Perminov (CoRR, 2020)

Higher-order and long-range synchronization effects for classification and computing in oscillator-based spiking neural networks. - Andrei Velichko; Vadim Putrolaynen; Maksim Belyaev (Neural Comput. Appl., 2021)

Detection of Risk Predictors of COVID-19 Mortality with Classifier Machine Learning Models Operated with Routine Laboratory Biomarkers. - Mehmet Tahir Huyut; Andrei Velichko; Maksim Belyaev (CoRR, 2022)

Machine Learning Sensors for Diagnosis of COVID-19 Disease Using Routine Blood Values for Internet of Things Application. - Andrei Velichko; Mehmet Tahir Huyut; Maksim Belyaev; Yuriy Izotov; Dmitry G. Korzun (Sensors, 2022)

Bifurcation and Entropy Analysis of a Chaotic Spike Oscillator Circuit Based on the S-Switch. - Petr Boriskov; Andrei Velichko; Nikolay Shilovsky; Maksim Belyaev (Entropy, 2022)

Entropy Approximation by Machine Learning Regression: Application for Irregularity Evaluation of Images in Remote Sensing. - Andrei Velichko; Maksim Belyaev; Matthias P. Wagner; Alireza Taravat (Remote. Sens., 2022)

Neural Network Entropy (NNetEn): Entropy-Based EEG Signal and Chaotic Time Series Classification, Python Package for NNetEn Calculation. - Andrei Velichko; Maksim Belyaev; Yuriy Izotov; Murugappan Murugappan; Hanif Heidari (Algorithms, 2023)

Neural Network Entropy (NNetEn): EEG Signals and Chaotic Time Series Separation by Entropy Features, Python Package for NNetEn Calculation. - Andrei Velichko; Maksim Belyaev; Yuriy Izotov; Murugappan Murugappan; Hanif Heidari (CoRR, 2023)

A Bio-Inspired Chaos Sensor Based on the Perceptron Neural Network: Concept and Application for Computational Neuro-science. - Andrei Velichko; Petr Boriskov; Maksim Belyaev; Vadim Putrolaynen (CoRR, 2023)

Imagery Tracking of Sun Activity Using 2D Circular Kernel Time Series Transformation, Entropy Measures and Machine Learning Approaches. - Irewola Aaron Oludehinwa; Andrei Velichko; Maksim Belyaev; Olasunkanmi I. Olusola (CoRR, 2023)

Entropy-based machine learning model for diagnosis and monitoring of Parkinson's Disease in smart IoT environment. - Maksim Belyaev; Murugappan Murugappan; Andrei Velichko; Dmitry G. Korzun (CoRR, 2023)

A Bio-Inspired Chaos Sensor Model Based on the Perceptron Neural Network: Machine Learning Concept and Application for Computational Neuro-Science. - Andrei Velichko; Petr Boriskov; Maksim Belyaev; Vadim Putrolaynen (Sensors, 2023)

Entropy-Based Machine Learning Model for Fast Diagnosis and Monitoring of Parkinson's Disease. - Maksim Belyaev; Murugappan Murugappan; Andrei Velichko; Dmitry G. Korzun (Sensors, 2023)

Objective Features Extracted from Motor Activity Time Series for Food Addiction Analysis Using Machine Learning. - Mikhail Borisenkov; Andrei Velichko; Maksim Belyaev; Dmitry G. Korzun; Tatyana Tserne; Larisa Bakutova; Denis Gubin (CoRR, 2024)

A Novel Approach for Estimating Positive Lyapunov Exponents in One-Dimensional Chaotic Time Series Using Machine Learning. - Andrey Velichko; Maksim Belyaev; Petr Boriskov (CoRR, 2025)