Interregional Transportation Modeling for the Far East of Russia Macro-region. - Andrey Velichko (DOOR (Supplement), 2016)

Software System for Interactive Simulation of Interregional Trade. - Andrey Velichko; Valeriya V. Gribova; Leonid A. Fedorishchev (DOOR (Supplement), 2016)

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)

Cloud Service for Interactive Simulation of Interregional Trade Flows. - Andrey Velichko; Valeriya V. Gribova; Leonid A. Fedorishchev (Autom. Control. Comput. Sci., 2019)

A method for the classification of chimera states of coupled oscillators and its application for creating a neural network information converter. - Andrei Velichko (CoRR, 2019)

Switch Elements with S-Shaped Current-Voltage Characteristic in Models of Neural Oscillators. - Petr Boriskov; Andrei Velichko (CoRR, 2019)

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)

Oscillator Circuit for Spike Neural Network with Sigmoid Like Activation Function and Firing Rate Coding. - Andrei Velichko; Petr Boriskov (CoRR, 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)

Reservoir Computing using High Order Synchronization of Coupled Oscillators. - A. A. Velichko; D. V. Ryabokon; S. D. Khanin; A. V. Sidorenko; A. G. Rikkiev (CoRR, 2020)

Neural Network for Low-Memory IoT Devices and MNIST Image Recognition Using Kernels Based on Logistic Map. - Andrei Velichko (CoRR, 2020)

Concept of LIF Neuron Circuit for Rate Coding in Spike Neural Networks. - Andrei Velichko; Petr Boriskov (IEEE Trans. Circuits Syst., 2020)

Recognition of handwritten MNIST digits on low-memory 2 Kb RAM Arduino board using LogNNet reservoir neural network. - Yuriy Izotov; A. A. Velichko; A. A. Ivshin; R. E. Novitskiy (CoRR, 2021)

An improved LogNNet classifier for IoT application. - Hanif Heidari; Andrei Velichko (CoRR, 2021)

A method for estimating the entropy of time series using artificial neural network. - Andrei Velichko; Hanif Heidari (CoRR, 2021)

A Method for Estimating the Entropy of Time Series Using Artificial Neural Networks. - Andrei Velichko; Hanif Heidari (Entropy, 2021)

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)

A Method for Medical Data Analysis Using the LogNNet for Clinical Decision Support Systems and Edge Computing in Healthcare. - Andrei Velichko (Sensors, 2021)

Two-Dimensional Neural Network Entropy for Remote Sensing Image Analysis. - Andrei Velichko; Matthias P. Wagner; Alireza Taravat (IGARSS, 2022)

Novel techniques for improvement the NNetEn entropy calculation for short and noisy time series. - Hanif Heidari; Andrei Velichko (CoRR, 2022)

A New Feature Selection Method for LogNNet and its Application for Diagnosis and Prognosis of COVID-19 Disease Using Routine Blood Values. - Mehmet Tahir Huyut; Andrei Velichko (CoRR, 2022)

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)

NNetEn2D: Two-Dimensional Neural Network Entropy in Remote Sensing Imagery and Geophysical Mapping. - Andrei Velichko; Matthias P. Wagner; Alireza Taravat; Bruce Hobbs; Alison Ord (Remote. Sens., 2022)

Diagnosis and Prognosis of COVID-19 Disease Using Routine Blood Values and LogNNet Neural Network. - Mehmet Tahir Huyut; Andrei Velichko (Sensors, 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)

Artificial Neural Networks for IoT-Enabled Smart Applications: Recent Trends. - Andrei Velichko; Dmitry G. Korzun; Alexander Meigal (Sensors, 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)

Entropy-statistical approach to phase-locking detection of pulse oscillations: application for the analysis of biosignal synchronization. - Petr Boriskov; Vadim Putrolaynen; Andrei Velichko; Kristina Peltonen (CoRR, 2024)

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)

Analysis of memristive maps with asymmetry. - Viet-Thanh Pham; Andrei Velichko; Van Van Huynh; Antonio Vincenzo Radogna; Giuseppe Grassi; Salah Mahmoud Boulaaras; Shaher Momani (Integr., 2024)

A compact structure for triple-memristor maps with a hyperplane of fixed points. - Viet-Thanh Pham; Jesús M. Muñoz-Pacheco; Andrei Velichko; Salah Mahmoud Boulaaras; Shaher Momani (Integr., 2025)

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)