Научно-образовательный центр математических моделей и методов теоретико-числовых систем
В лаборатории разрабатываются перспективные подходы к улучшению эксплуатационных и качественных показателей систем цифровой обработки сигналов и изображений. Осуществляется математическое, программное и аппаратное моделирование высокопроизводительных вычислительных систем. Особое внимание уделяется разработке методов искусственного интеллекта для решения прикладных задач сельского хозяйства и медицины.
Применение искусственного интеллекта для решения прикладных задач
Применение разработок при создании систем интеллектуальной обработки гетерогенных данных для решения различных прикладных задач в сельском хозяйстве и медицине, основанных на нейросетевом анализе сигналов и изображений.
Разработка методов и алгоритмов интеллектуального анализа сигналов и изображений
Разработка мультимодальных нейросетевых архитектур с использованием алгоритмов обработки гетерогенных данных для улучшения интеллектуального анализа сигналов и изображений. Улучшение существующих методов и алгоритмов безградиентной оптимизации и градиентной оптимизации на основе дробно-рациональных производных для ускорения и улучшения обучения глубоких нейронных сетей.
Разработка высокопроизводительных устройств цифровой обработки сигналов и изображений:
Модификация архитектур вычислительных элементов, используемых в современных высокоскоростных устройствах обработки сигналов и изображений. Адаптация разработанных методов и архитектур для высокоскоростных параллельных вычислений по нескольким каналам в системе остаточных классов. Совершенствование подходов к одномерной и многомерной свертке за счет развития методологии Винограда для реализации матричных вычислений с пониженной вычислительной сложностью при обработке сигналов и изображений.
Методы исследований:
1. Математическое моделирование
2. Анализ больших данных
3. Машинное обучение
4. Искусственный интеллект
5. Статистический анализ
6. Проектирование сверхбольших интегральных схем
7. Цифровая обработка сигналов
8. Цифровая обработка изображений
9. Цифровая фильтрация
Коллектив:
Ляхов Павел Алексеевич
Заведующий лабораторией
Федоренко Владимир Васильевич
Ведущий научный сотрудник
Нагорнов Николай Николаевич
Старший научный сотрудник
Калита Диана Ивановна
Старший научный сотрудник
Оразаев Анзор Русланович
Младший научный сотрудник
Мария Романовна
Младший научный сотрудник
Ульяна Ляхова
Младший научный сотрудник
Публикации и патенты
Публикации:
2025 г.
The Method of Ensembling Neural Networks, D Reznikov, P Lyakhov, R Abdulkadirov, Current Problems of Applied Mathematics and Computer Systems: CPAMCS 2024, цитирований: 233, 2025
Transformer operator network with fast difference gradient positive–negative momentum for solving Navier–Stokes equations, R Abdulkadirov, P Lyakhov, M Bergerman, N Nagornov, Chaos, Solitons & Fractals 200, 116964, цитирований: 0, 2025
A Systematic Review of Methods and Algorithms for the Intelligent Processing of Agricultural Data Applied to Sunflower Crops, V Arustamyan, P Lyakhov, U Lyakhova, R Abdulkadirov, V Rybin, ..., Machine Learning and Knowledge Extraction 7 (4), 130, цитирований: 0, 2025
The Structural Similarity Can Identify the Presence of Noise in Video Data from Unmanned Vehicles, A Orazaev, P Lyakhov, V Andreev, D Butusov, Journal of Imaging 11 (11), 375, цитирований: 0, 2025
Повышение скорости вейвлет-обработки изображений на основе метода Винограда с учетом децимации, ПА Ляхов, Известия Юго-Западного государственного университета 29 (2), 130-145, цитирований: 0, 2025
Designing of High-Performance Digital Filters using the Balanced Residue Number System Moduli Set, PA Lyakhov, NN Nagornov, MV Bergerman, AS Abdulsalyamova, ..., Programming and Computer Software 51 (5), 327-339, цитирований: 0, 2025
Physics-informed neural network model using natural gradient descent with Dirichlet distribution, R Abdulkadirov, P Lyakhov, V Baboshina, Engineering Analysis with Boundary Elements 178, 106282, цитирований: 0, 2025
Enhancing Drone Detection via Transformer Neural Network and Positive–Negative Momentum Optimizers, P Lyakhov, D Butusov, V Pismennyy, R Abdulkadirov, N Nagornov, ..., Big Data and Cognitive Computing 9 (7), 167, цитирований: 0, 2025
Ensemble System for Skin Cancer Detection Based on the Analysis of Heterogeneous Dermatological Data Using Multimodal Neural Networks, PA Lyakhov, UA Lyakhova, DI Kalita, Automatic Control and Computer Sciences 59 (3), 328-339, цитирований: 0, 2025
Comparative Analysis of Vegetation Indices on Agricultural Images of Different Modalities, P Lyakhov, A Orazaev, V Baboshina, S Odintcov, A Esaulko, International Conference on Innovations in Sustainable Agricultural Systems …, цитирований: 0, 2025
Physics-Aware Machine Learning Approach for High-Precision Quadcopter Dynamics Modeling, R Abdulkadirov, P Lyakhov, D Butusov, N Nagornov, D Kalita, Drones 9 (3), 187, цитирований: 2, 2025
Enhancing Unmanned Aerial Vehicle Object Detection via Tensor Decompositions and Positive–Negative Momentum Optimizers, R Abdulkadirov, P Lyakhov, D Butusov, N Nagornov, D Reznikov, ..., Mathematics 13 (5), цитирований: 1, 2025
Analysis of video data of an unmanned aerial vehicle based on the structural similarity index, P Lyakhov, A Orazaev, Computers. Optics 49, 624-633, цитирований: 1, 2025
A Multimodal Neural Network for Classification of Electrocardiogram Signals with Preliminary Feature Extraction, PA Lyakhov, MR Kiladze, DI Kaplun, in Sustainable Development, Innovation and Green Technology (ICASDIGT-2024), 285, цитирований: 0, 2025
Detection of attention state in children with autism spectrum disorder based on neural network classification of electroencephalograms, PA Lyakhov, UA Lyakhova, VA Baboshina, VV Baryshev, NN Nagornov, Вестник Санкт-Петербургского университета. Прикладная математика …, цитирований: 0, 2025
Bidirectional Encoder representation from Image Transformers for recognizing sunflower diseases from photographs, VA Baboshina, PA Lyakhov, UA Lyakhova, VA Pismennyy, Компьютерная оптика 49 (3), 435-442, цитирований: 2, 2025
2024 г.
Improving the accuracy of neural network pattern recognition by fractional gradient descent, RI Abdulkadirov, PA Lyakhov, VA Baboshina, NN Nagornov, IEEE Access 12, 168428-168444, цитирований: 3, 2024
Systematic review of approaches to detection and classification of skin cancer using artificial intelligence: Development and prospects, UA Lyakhova, PA Lyakhov, Computers in Biology and Medicine 178, 108742, цитирований: 33, 2024
Modern trends in improving the technical characteristics of devices and systems for digital image processing, NN Nagornov, PA Lyakhov, MV Bergerman, DI Kalita, IEEE Access 12, 44659-44681, цитирований: 4, 2024
Satellite image recognition using ensemble neural networks and difference gradient positive-negative momentum, R Abdulkadirov, P Lyakhov, M Bergerman, D Reznikov, Chaos, Solitons & Fractals 179, 114432, цитирований: 9, 2024
Efficient design and implementation of a reversible switched network in quantum cellular automata technology, M Vahabi, E Rahimi, P Lyakhov, Journal of King Saud University-Computer and Information Sciences 36 (1), 101910, цитирований: 9, 2024
Comparative Analysis of Fast Matrix Multiplication Methods on Different Datatypes, A Abdulsalyamova, R Abdulkadirov, P Lyakhov, N Nagornov, Conference on Current Problems of Applied Mathematics and Computer Systems …, цитирований: 0, 2024
The Method of Ensembling Neural Networks for Pattern Recognition, D Reznikov, P Lyakhov, R Abdulkadirov, Conference on Current Problems of Applied Mathematics and Computer Systems …, цитирований: 0, 2024
Improving the Balance of RNS by Using the Metric of Finding Optimal Sets of Low-Cost and 2 k+ 1 Modules, A Abdulsalyamova, M Bergerman, P Lyakhov, Conference on Current Problems of Applied Mathematics and Computer Systems …, цитирований: 0, 2024
Video Analysis of an Unmanned Aerial Vehicle in Low Signal Conditions, P Lyakhov, A Orazaev, N Nagornov, Conference on Current Problems of Applied Mathematics and Computer Systems …, цитирований: 0, 2024
Enhancing the Pattern Recognition on Unmanned Aerial Vehicle Images of Agricultural Objects by Positive–Negative Momentum, R Abdulkadirov, P Lyakhov, D Kalita, International Conference on Innovations in Sustainable Agricultural Systems …, цитирований: 0, 2024
Ensemble of Visual Transformer and Deep Neural Networks for Recognizing Sunflower Diseases from Photographs, VA Baboshina, PA Lyakhov, DI Kaplun, NIELIT's International Conference on Communication, Electronics and Digital …, цитирований: 1, 2024
Neural network recognition system for video transmitted through a binary symmetric channel, VA Baboshina, AR Orazaev, PA Lyakhov, EE Boyarskaya, Компьютерная оптика 48 (4), 582-591, цитирований: 0, 2024
Multimodal ensemble neural network system for skin cancer detection on heterogeneous dermatological data, UA Lyakhova, PA Lyakhov, Vestnik Sankt-Peterburgskogo Universiteta. Seriya 10. Prikladnaya Matematika …, цитирований: 1, 2024
Non-convex optimization with using positive-negative moment estimation and its application for skin cancer recognition with a neural network, PA Lyakhov, UA Lyakhova, RI Abdulkadirov, Computer Optics 48 (2), 260-271, цитирований: 9, 2024
2023 г.
Multimodal Analysis of Unbalanced Dermatological Data for Skin Cancer Recognition, PA Lyakhov, UA Lyakhova, DI Kalita, IEEE Access 11, 131487-131507, цитирований: 24, 2023
Survey of Optimization Algorithms in Modern Neural Networks, R Abdulkadirov, P Lyakhov, N Nagornov, Mathematics 11 (11), 2466, цитирований: 118, 2023
A novel QCA circuit-switched network with power dissipation analysis for nano communication applications, M Vahabi, E Rahimi, P Lyakhov, A Otsuki, Nano Communication Networks 35, 100438, цитирований: 21, 2023
Residue number systems with six modules and efficient circuits based on power-of-two diagonal modulus, P Boyvalenkov, P Lyakhov, N Semyonova, M Valueva, G Boyvalenkov, D Minenkov, D Kaplun, Computers and Electrical Engineering 110, 108854, цитирований: 4, 2023
Neural Network System for Recognizing Images Affected by Random-Valued Impulse Noise, A Orazaev, P Lyakhov, V Baboshina, D Kalita, Applied Sciences 13 (3), 1585, цитирований: 9, 2023
Novel Quantum-Dot Cellular Automata-Based Gate Designs for Efficient Reversible Computing, M Vahabi, E Rahimi, P Lyakhov, AN Bahar, KA Wahid, A Otsuki, Sustainability 15 (3), 2265, цитирований: 18, 2023
High-Speed Wavelet Image Processing Using the Winograd Method with Downsampling, P Lyakhov, N Semyonova, N Nagornov, M Bergerman, A Abdulsalyamova, Mathematics 11 (22), 4644, цитирований: 1, 2023
Multimodal Neural Network for Recognition of Cardiac Arrhythmias Based on 12-Load Electrocardiogram Signals, MR Kiladze, UA Lyakhova, PA Lyakhov, NN Nagornov, M Vahabi, IEEE Access 11, 133744-133754, цитирований: 12, 2023
A novel sign detection method in residue number system based on Chinese remainder theorem with fractional values, P Lyakhov, M Bergerman, R Abdulkadirov, A Abdulsalyamova, N Nagornov, A Voznesensky, D Minenkov, D Kaplun, Microprocessors and Microsystems 102, 104940, цитирований: 1, 2023
Area-Efficient digital filtering based on truncated multiply-accumulate units in residue number system 2n-1, 2n, 2n+ 1, PA Lyakhov, Journal of King Saud University-Computer and Information Sciences 35 (6), 101574, цитирований: 5, 2023
Reducing the Computational Complexity of Image Processing Using Wavelet Transform Based on the Winograd Method, PA Lyakhov, NN Nagornov, NF Semyonova, AS Abdulsalyamova, Pattern Recognition and Image Analysis 33 (2), 184-191, цитирований: 4, 2023
Neural network system for analyzing statistical factors of patients for predicting the survival of dental implants, PA Lyakhov, AA Dolgalev, UA Lyakhova, AA Muraev, KE Zolotayev, DY Semerikov, Frontiers in Neuroinformatics, цитирований: 30, 2023
A new approach to training neural networks using natural gradient descent with momentum based on Dirichlet distributions, RI Abdulkadirov, PA Lyakhov, Computer Optics 47 (1), 160-169, цитирований: 12, 2023
New method for detecting and removing random-valued impulse noise from images, PA Lyakhov, AR Orazaev, Computer Optics 47 (2), 262-271, цитирований: 4, 2023
Development of digital image processing algorithms based on the Winograd method in general form and analysis of their computational complexity, PA Lyakhov, NN Nagornov, NF Semyonova, AS Abdulsalyamova, Computer Optics 47 (1), 68-78, цитирований: 7, 2023
Reliable Kalman Filtering with Conditionally Local Calculations in Wireless Sensor Networks, PA Lyakhov, DI Kalita, Automatic Control and Computer Sciences 57 (2), 154-166, цитирований: 1, 2023
Solving Poisson Equation by Physics-Informed Neural Network with Natural Gradient Descent with Momentum, RI Abdulkadirov, PA Lyakhov, NN Nagornov, 2023 Seminar on Signal Processing, 3-6, цитирований: 1, 2023
Increasing the Speed of Wavelet Image Processing with Decimation Using the Winograd Method, PA Lyakhov, NN Nagornov, NF Semyenova, AS Abdulsalyamova, 2023 Seminar on Signal Processing, 79-82, цитирований: 1, 2023
Raw Data Point Cloud Probabilistic Filtering Algorithm, DI Kalita, PA Lyakhov, NN Nagornov, 2023 Seminar on Signal Processing, 27-31, цитирований: 0, 2023
Comparative Analysis of Computational Complexity of Fast Matrix Multiplication Algorithms, AS Abdulsalyamova, DI Kalita, PA Lyakhov, NN Nagornov, MV Bergerman, 2023 International Conference on Quality Management, Transport and …, цитирований: 0, 2023
Multimodal Neural Network System for Skin Cancer Recognition with a Modified Cross-Entropy Loss Function, P Lyakhov, U Lyakhova, D Kalita, Preprints, цитирований: 5, 2023
2022 г.
System for the Recognizing of Pigmented Skin Lesions with Fusion and Analysis of Heterogeneous Data Based on a Multimodal Neural Network, PA Lyakhov, UA Lyakhova, NN Nagornov, Cancers 14 (7), 1819, цитирований: 27, 2022
RNS-Based FPGA Accelerators for High-Quality 3D Medical Image Wavelet Processing Using Scaled Filter Coefficients, NN Nagornov, PA Lyakhov, MV Valueva, MV Bergerman, IEEE Access 10, 19215-19231, цитирований: 20, 2022
Moving Object Detection Based on a Combination of Kalman Filter and Median Filtering, D Kalita, P Lyakhov, Big Data and Cognitive Computing 6 (4), 142, цитирований: 9, 2022
Accelerating Extreme Search of Multidimensional Functions Based on Natural Gradient Descent with Dirichlet Distributions, R Abdulkadirov, P Lyakhov, N Nagornov, Mathematics 10 (19), 3556, цитирований: 9, 2022
Estimates of Mild Solutions of Navier–Stokes Equations in Weak Herz-Type Besov–Morrey Spaces, R Abdulkadirov, P Lyakhov, Mathematics 10 (5), 680, цитирований: 12, 2022
High Performance Parallel Pseudorandom Number Generator on Cellular Automata, A Levina, D Mukhamedjanov, D Bogaevskiy, P Lyakhov, M Valueva, D Kaplun, Symmetry 14 (9), 1869, цитирований: 13, 2022
Novel Reversible Comparator Design in Quantum Dot-Cellular Automata with Power Dissipation Analysis, M Vahabi, P Lyakhov, AN Bahar, A Otsuki, KA Wahid, Applied Sciences 12 (15), 7846, цитирований: 12, 2022
High-performance digital image filtering architectures in the residue number system based on the Winograd method, MV Valueva, PA Lyakhov, NN Nagornov, GV Valuev, Computer Optics 46 (5), 752-762, цитирований: 8, 2022
On the Computational Complexity of 2D Filtering by Winograd Method, PA Lyakhov, AS Abdulsalyamova, NF Semyonova, NN Nagornov, AS Voznesensky, DI Kaplun, 2022 11th Mediterranean Conference on Embedded Computing (MECO), 1-4, цитирований: 8, 2022
Bilateral and Median Filter Combination for High-Quality Cleaning of Random Impulse Noise in Images, PA Lyakhov, AS Voznesensky, ED Shalugin, AR Orazaev, VA Baboshina, 2022 11th Mediterranean Conference on Embedded Computing (MECO), 1-5, цитирований: 4, 2022
Comparative Analysis of Despeckle Filtering Methods for Ultrasound Images, VA Baboshina, PA Lyakhov, DI Kalita, 2022 International Conference on Quality Management, Transport and …, цитирований: 3, 2022
Theoretical Analysis of the Convolutional Neural Networks Acceleration by Organizing Calculations According to the Winograd Method, AS Abdulsalyamova, PA Lyakhov, DI Kalita, 2022 International Conference on Quality Management, Transport and …, цитирований: 2, 2022
Acceleration of Signal Prediction in Wireless Sensor Networks Based on Kalman Filter and Goldschmidt Algorithm, DI Kalita, PA Lyakhov, 2022 International Conference on Quality Management, Transport and …, цитирований: 0, 2022
Efficient Probabilistic Filtering of Data Subject to Channel Noise Under Local Pooling Conditions, PA Lyakhov, DI Kalita, AM Sinitca, AS Voznesensky, 2022 11th Mediterranean Conference on Embedded Computing (MECO), 1-5, цитирований: 0, 2022
Improving extreme search with natural gradient descent using Dirichlet distribution, RI Abdulkadirov, PA Lyakhov, International Conference on Mathematics and its Applications in new Computer …, цитирований: 7, 2022
Neural Network Classification of Dermatoscopic Images of Pigmented Skin Lesions, PA Lyakhov, UA Lyakhova, VA Baboshina, International Conference on Mathematics and its Applications in new Computer …, цитирований: 1, 2022
Hardware Implementation of the Kalman Filter for Video Signal Processing, P Lyakhov, D Kalita, M Bergerman, International Conference on Mathematics and its Applications in new Computer …, цитирований: 1, 2022
Comparison of Approaches to the Circuits Design for DWT with CDF 9/7 Wavelet, P Lyakhov, N Nagornov, M Bergerman, International Conference on Mathematics and its Applications in new Computer …, цитирований: 1, 2022
CRTf-Based Reverse Converter for RNS with Low-Cost Modules, M Bergerman, P Lyakhov, N Semyonova, D Bogaevskiy, D Kaplun, International Conference on Mathematics and its Applications in new Computer …, цитирований: 1, 2022
On the Algorithmic Complexity of Digital Image Processing Filters with Winograd Calculations, P Lyakhov, A Abdulsalyamova, International Conference on Mathematics and its Applications in new Computer …, цитирований: 3, 2022
Special Issue on Advanced Information Processing Methods and Their Applications, P Lyakhov, Applied Sciences 12 (18), 9090, цитирований: 2, 2022
Special Issue on Mathematics and Digital Signal Processing, P Lyakhov, Applied Sciences 12 (18), 9033, цитирований: 2, 2022
2021 г.
Accelerating Extreme Search Based on Natural Gradient Descent with Beta Distribution, P Lyakhov, R Abdulkadirov, 2021 International Conference Engineering and Telecommunication (En&T), 1-5, цитирований: 2, 2021
A Method of Increasing Digital Filter Performance Based on Truncated Multiply-Accumulate Units, P Lyakhov, M Valueva, G Valuev, N Nagornov, Applied Sciences (Switzerland), цитирований: 15, 2021
High-Performance Digital Filtering on Truncated Multiply-Accumulate Units in the Residue Number System, P Lyakhov, M Valueva, G Valuev, N Nagornov, IEEE Access, цитирований: 21, 2021
System for Neural Network Determination of Atrial Fibrillation on ECG Signals with Wavelet-Based Preprocessing, P Lyakhov, M Kiladze, U Lyakhova, Applied Sciences (Switzerland), цитирований: 16, 2021
Design and Implementation of Novel Efficient Full Adder/Subtractor Circuits Based on Quantum-Dot Cellular Automata Technology, M Vahabi, P Lyakhov, A Bahar, Applied Sciences (Switzerland), цитирований: 23, 2021
Removal of Ocular Artifacts from the Electroencephalogram Signal Flow using Median Filtering, PA Lyakhov, M Kialdze, DI Kaplun, AS Voznesensky, International Conference Automatics and Informatics (ICAI), цитирований: 0, 2021
A New Method of Sign Detection in RNS Based on Modified Chinese Remainder Theorem, PA Lyakhov, MV Valueva, DI Kaplun, AS Voznesensky, Mediterranean Conference on Embedded Computing (MECO), цитирований: 0, 2021
Design Reverse Converter for Balanced RNS with Three Low-cost Modules, P Lyakhov, M Bergerman, N Semyonova, D Kaplun, A Voznesensky, Mediterranean Conference on Embedded Computing (MECO), цитирований: 2, 2021
Single Image Super-Resolution Method Based on Bilinear Interpolation and U-Net Combination, PA Lyakhov, GV Valuev, MV Valueva, DI Kaplun, AM Sinitca, 2021 10th Mediterranean Conference on Embedded Computing (MECO), цитирований: 5, 2021
Pulmonary Fibrosis Progression Prognosis Using Machine Learning, A Glotov, P Lyakhov, Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT), цитирований: 4, 2021
Method of Cleaning Hair Structures for Intellectual Image Classification of Skin Neoplasms, UA Lyakhova, PA Lyakhov, Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT), цитирований: 1, 2021
2020 г.
Application of the residue number system to reduce hardware costs of the convolutional neural network implementation, MV Valueva, NN Nagornov, PA Lyakhov, GV Valuev, NI Chervyakov, Mathematics and Computers in Simulation, цитирований: 359, 2020
Residue Number System-Based Solution for Reducing the Hardware Cost of a Convolutional Neural Network, NI Chervyakov, PA Lyakhov, MA Deryabin, NN Nagornov, MV Valueva, GV Valuev, Neurocomputing, цитирований: 18, 2020
Analysis of the Quantization Noise in Discrete Wavelet Transform Filters for 3D Medical Imaging, N Chervyakov, P Lyakhov, N Nagornov, Applied Sciences (Switzerland), цитирований: 43, 2020
A Division Algorithm in a Redundant Residue Number System Using Fractions, N Chervyakov, P Lyakhov, M Babenko, I Lavrinenko, M Deryabin, A Lavrinenko, A Nazarov, M Valueva, A Voznesensky, D Kaplun, Applied Sciences (Switzerland), цитирований: 2, 2020
Low-Bit Hardware Implementation of DWT for 3D Medical Images Processing, PA Lyakhov, MV Valueva, NN Nagornov, NI Chervyakov, DI Kaplun, 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus), цитирований: 5, 2020
A New Method of Cleaning Video from Impulse Noise, NI Chervyakov, PA Lyakhov, AR Orazaev, MV Valueva, 2019 International Conference on Engineering and Telecommunication (EnT), цитирований: 1, 2020
High-Quality 3D Medical Imaging by Wavelet Filters with Reduced Coefficients Bit-Width, NI Chervyakov, PA Lyakhov, NN Nagornov, MV Valueva, International Conference on Engineering and Telecommunication (EnT), цитирований: 0, 2020
2019 г.
Construction of Residue Number System Using Hardware Efficient Diagonal Function, M Valueva, G Valuev, N Semyonova, P Lyakhov, N Chervyakov, D Kaplun, D Bogaevskiy, Electronics (Switzerland), цитирований: 12, 2019
A High-Speed Division Algorithm for Modular Numbers Based on the Chinese Remainder Theorem with Fractions and Its Hardware Implementation, N Chervyakov, P Lyakhov, M Babenko, A Nazarov, M Deryabin, I Lavrinenko, A Lavrinenko, Electronics (Switzerland), цитирований: 12, 2019
Implementation of Smoothing Image Filtering in the Residue Number System, NI Chervyakov, PA Lyakhov, NN Nagornov, DI Kaplun, AS Voznesenskiy, DV Bogayevskiy, 2019 8th Mediterranean Conference on Embedded Computing (MECO), цитирований: 5, 2019
Hardware Implementation of Video Processing Device using Residue Number System, DI Kaplun, NI Chervyakov, PA Lyakhov, AS Ionisyan, MV Valueva, VV Gulvanskiy, P Rangababu, International Conference on Telecommunications and Signal Processing (TSP), цитирований: 3, 2019
Analysis of the Quantization Noise of Linear Time-Invariant Filters for Image Processing, PA Lyakhov, NN Nagornov, NI Chervyakov, DI Kaplun, IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus), цитирований: 3, 2019
A New Method for Adaptive Median Filtering of Images, PA Lyakhov, AR Orazaev, NI Chervyakov, DI Kaplun, 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus), цитирований: 13, 2019
2018 г.
Area-Efficient FPGA Implementation of Minimalistic Convolutional Neural Network Using Residue Number System, NI Chervyakov, PA Lyakhov, MV Valueva, GV Valuev, DI Kaplun, GA Efimenko, DV Gnezdilov, PROCEEDINGS OF THE 24TH CONFERENCE OF OPEN INNOVATIONS ASSOCIATION (FRUCT), цитирований: 8, 2018
Analysis of the Quantization Noise in Discrete Wavelet Transform Filters for Image Processing, N Chervyakov, P Lyakhov, D Kaplun, D Butusov, N Nagornov, Electronics (Switzerland), цитирований: 34, 2018
The architecture of a fault-tolerant modular neurocomputer based on modular number projections, NI Chervyakov, PA Lyakhov, MG Babenko, IN Lavrinenko, AV Lavrinenko, AS Nazarov, Neurocomputing, цитирований: 20, 2018
A new model to optimize the architecture of a fault-tolerant modular neurocomputer, NI Chervyakov, PA Lyakhov, MG Babenko, IN Lavrinenko, AV Lavrinenko, MA Deryabin, AS Nazarov, Neurocomputing, цитирований: 7, 2018
Efficient RNS Reverse Converters for Moduli Sets with Dynamic Ranges Up to (10n+1)-bit, H Pettenghi, R Paludo, R Matos, PA Lyakhov, Circuits, Systems, and Signal Processing, цитирований: 2, 2018
2017 г.
Increasing of convolutional neural network performance using residue number system, NI Chervyakov, PA Lyakhov, MV Valueva, 2017 International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON), цитирований: 18, 2017
Efficient implementation of modular multiplication by constants applied to RNS reverse converters, R de Matos, R Paludo, N Chervyakov, PA Lyakhov, H Pettenghi, 2017 IEEE International Symposium on Circuits and Systems (ISCAS), цитирований: 9, 2017
RNS-Based Image Processing, N Chervyakov, P Lyakhov, Embedded Systems Design with Special Arithmetic and Number Systems, цитирований: 5, 2017
On RNS with VLSI-friendly diagonal function, NI Chervyakov, PA Lyakhov, NF Semyonova, MV Valueva, International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON), цитирований: 1, 2017
Efficiency analysis of the image impulse noise cleaning using median filters with weighted central element, NI Chervyakov, PA Lyakhov, AR Orazaev, MV Valueva, 2017 International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON), цитирований: 5, 2017
2016 г.
Residue-to-binary conversion for general moduli sets based on approximate Chinese remainder theorem, NI Chervyakov, AS Molahosseini, PA Lyakhov, MG Babenko, MA Deryabin, International Journal of Computer Mathematics, цитирований: 42, 2016
An efficient method of error correction in fault-tolerant modular neurocomputers, NI Chervyakov, PA Lyakhov, MG Babenko, AI Garyanina, IN Lavrinenko, AV Lavrinenko, MA Deryabin, Neurocomputing, цитирований: 22, 2016
Effect of RNS dynamic range on grayscale images filtering, NI Chervyakov, PA Lyakhov, DI Kalita, KS Shulzhenko, 2016 XV International Symposium Problems of Redundancy in Information and Control Systems (REDUNDANCY), цитирований: 3, 2016
High-speed smoothing filter in the Residue Number System, NI Chervyakov, PA Lyakhov, AS Ionisyan, MV Valueva, Third International Conference on Digital Information Processing, Data Mining, and Wireless Communications (DIPDMWC), цитирований: 4, 2016
2015 г.
Comparison of modular numbers based on the chinese remainder theorem with fractional values, NI Chervyakov, AS Molahosseini, PA Lyakhov, MG Babenko, IN Lavrinenko, AV Lavrinenko, Automatic Control and Computer Sciences, цитирований: 4, 2015
Effect of RNS moduli set selection on digital filter performance for satellite communications, NI Chervyakov, PA Lyakhov, DI Kalita, KS Shulzhenko, International Siberian Conference on Control and Communications (SIBCON), цитирований: 1, 2015
2014 г.
FIR Filters in Two-Stage Residue Number System, NI Chervyakov, PA Lyakhov, KS Shulzhenko, International Conference on Engineering and Telecommunication (EnT), цитирований: 1, 2014
An Approximate Method for Comparing Modular Numbers and its Application to the Division of Numbers in Residue Number Systems, NI Chervyakov, MG Babenko, PA Lyakhov, IN Lavrinenko, Cybernetics and Systems Analysis, цитирований: 32, 2014
Digital filtering of images in a residue number system using finite-field wavelets, NI Chervyakov, PA Lyakhov, MG Babenko, Automatic Control and Computer Sciences, цитирований: 23, 2014
Патенты:
Способ адаптивной медианной фильтрации импульсного шума на изображениях
Павел Алексеевич Ляхов, Анзор Русланович Оразаев, Ульяна Алексеевна Ляхова, Мария Васильевна Валуева
RU2771791C1, 2022