Alexey V. Serenko

According to our database, Alexey V. Serenko authored at least 12 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

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., February, 2025

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

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., March, 2024

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

Proceedings of the Neural Information Processing - 31st International Conference, 2024

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, September, 2023

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

2022

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

Proceedings of the International Conference on Computational Science and Computational Intelligence, 2022

2018

Spiking neural network reinforcement learning method based on temporal coding and STDP.

Alexander G. Sboev, Danila Vlasov, Roman B. Rybka, Alexey V. Serenko

Proceedings of the Postproceedings of the 9th Annual International Conference on Biologically Inspired Cognitive Architectures, 2018

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

Proceedings of the Postproceedings of the 9th Annual International Conference on Biologically Inspired Cognitive Architectures, 2018

2017

Solving a classification task by spiking neurons with STDP and temporal coding.

Alexander G. Sboev, Danila Vlasov, Roman B. Rybka, Alexey V. Serenko

Proceedings of the 8th Annual International Conference on Biologically Inspired Cognitive Architectures, 2017

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

Proceedings of the 8th Annual International Conference on Biologically Inspired Cognitive Architectures, 2017

2016

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

Proceedings of the International Conference on Computational Science 2016, 2016