Evaluation of the Cardiovascular Risk in Middle-aged Workers: An Artificial Neural Networks-based Approach. - Anton Selivanov; Aleksander G. Sboev; Svetlana Gorokhova; Viktor Pfaf; Dmitry Gudovskikh; Roman B. Rybka; Aleksey V. Serenko; Ivan Moloshnikov (ICCS, 2016)

To the role of the choice of the neuron model in spiking network learning on base of Spike-Timing-Dependent Plasticity. - Alexander G. Sboev; Roman B. Rybka; Alexey V. Serenko; Danila Vlasov; Nikolay A. Kudryashov; Vyacheslav A. Demin (BICA, 2017)

Solving a classification task by spiking neurons with STDP and temporal coding. - Alexander G. Sboev; Danila Vlasov; Roman B. Rybka; Alexey V. Serenko (BICA, 2017)

Estimation of the influence of spiking neural network parameters on classification accuracy using a genetic algorithm. - Aleksander G. Sboev; Alexey V. Serenko; Roman B. Rybka; Danila Vlasov; Andrey Filchenkov (BICA, 2018)

Spiking neural network reinforcement learning method based on temporal coding and STDP. - Alexander G. Sboev; Danila Vlasov; Roman B. Rybka; Alexey V. Serenko (BICA, 2018)

Spoken Digits Classification Based on Spiking Neural Networks with Memristor-Based STDP. - Danila Vlasov; Yury Davydov; Alexey V. Serenko; Roman B. Rybka; Alexander G. Sboev (CSCI, 2022)

Extraction of Significant Features by Fixed-Weight Layer of Processing Elements for the Development of an Efficient Spiking Neural Network Classifier. - Alexander G. Sboev; Roman B. Rybka; Dmitry Kunitsyn; Alexey V. Serenko; Vyacheslav Ilyin; Vadim Putrolaynen (Big Data Cogn. Comput., 2023)

Memristor-based spiking neural network with online reinforcement learning. - Danila Vlasov; Anton A. Minnekhanov; Roman B. Rybka; Yury Davydov; Alexander G. Sboev; Alexey V. Serenko; Alexander Ilyasov; Vyacheslav A. Demin (Neural Networks, 2023)

Direct Correlational Spike-Timing-Dependent Plasticity Learning Applied to Classification Tasks. - Alexander G. Sboev; Dmitry Kunitsyn; Yury Davydov; Danila Vlasov; Alexey V. Serenko; Roman B. Rybka; Yuanchao Liu (ICONIP (2), 2024)

Comparison of Bagging and Sparcity Methods for Connectivity Reduction in Spiking Neural Networks with Memristive Plasticity. - Roman B. Rybka; Yury Davydov; Danila Vlasov; Alexey V. Serenko; Alexander G. Sboev; Vyacheslav Ilyin (Big Data Cogn. Comput., 2024)

Combination of reward-modulated spike-timing dependent plasticity and temporal difference long-term potentiation in actor-critic spiking neural network. - Yunes Tihomirov; Roman B. Rybka; Alexey V. Serenko; Alexander G. Sboev (Cogn. Syst. Res., 2025)

Evaluation of the Accuracy of Converting a Traditional Neural Network into a Pulsed One with Different Methods for Selecting the Neuron Threshold. - Roman B. Rybka; Alexey V. Serenko; Aleksandr V. Naumov; Alexander G. Sboev (Autom. Remote. Control., 2025)