Digital filtering of images in a residue number system using finite-field wavelets. - Nikolay I. Chervyakov; Pavel Alekseevich Lyakhov; Mikhail G. Babenko (Autom. Control. Comput. Sci., 2014)

Comparison of modular numbers based on the chinese remainder theorem with fractional values. - Nikolay I. Chervyakov; Amir Sabbagh Molahosseini; Pavel Alekseevich Lyakhov; Mikhail G. Babenko; Irina N. Lavrinenko; Anton V. Lavrinenko (Autom. Control. Comput. Sci., 2015)

An efficient method of error correction in fault-tolerant modular neurocomputers. - Nikolay I. Chervyakov; Pavel Alekseevich Lyakhov; Mikhail G. Babenko; A. I. Garyanina; Irina N. Lavrinenko; Anton V. Lavrinenko; Maxim Anatolievich Deryabin (Neurocomputing, 2016)

Efficient implementation of modular multiplication by constants applied to RNS reverse converters. - Roberto de Matos; Rogerio Paludo; Nikolay I. Chervyakov; Pavel Alekseevich Lyakhov; Héctor Pettenghi (ISCAS, 2017)

Residue-to-binary conversion for general moduli sets based on approximate Chinese remainder theorem. - Nikolay I. Chervyakov; Amir Sabbagh Molahosseini; Pavel Alekseevich Lyakhov; Mikhail G. Babenko; Maxim Anatolievich Deryabin (Int. J. Comput. Math., 2017)

Area-Efficient FPGA Implementation of Minimalistic Convolutional Neural Network Using Residue Number System. - Nikolay I. Chervyakov; Pavel Alekseevich Lyakhov; Maria V. Valueva; Georgii V. Valuev; Dmitrii I. Kaplun; George A. Efimenko; Denis V. Gnezdilov (FRUCT, 2018)

Efficient RNS Reverse Converters for Moduli Sets with Dynamic Ranges Up to ((10n+1) ) -bit. - Héctor Pettenghi; Rogerio Paludo; Roberto de Matos; Pavel Alekseevich Lyakhov (Circuits Syst. Signal Process., 2018)

A new model to optimize the architecture of a fault-tolerant modular neurocomputer. - Nikolay I. Chervyakov; Pavel Alekseevich Lyakhov; Mikhail G. Babenko; Irina N. Lavrinenko; Anton V. Lavrinenko; Maxim Anatolievich Deryabin; Anton S. Nazarov (Neurocomputing, 2018)

The architecture of a fault-tolerant modular neurocomputer based on modular number projections. - Nikolay I. Chervyakov; Pavel Alekseevich Lyakhov; Mikhail G. Babenko; Irina N. Lavrinenko; Anton V. Lavrinenko; Anton S. Nazarov (Neurocomputing, 2018)

Implementation of Smoothing Image Filtering in the Residue Number System. - Nikolay I. Chervyakov; Pavel Alekseevich Lyakhov; Nikolay N. Nagornov; Dmitrii I. Kaplun; Alexander S. Voznesenskiy; Danil V. Bogayevskiy (MECO, 2019)

Hardware Implementation of Video Processing Device using Residue Number System. - Dmitrii I. Kaplun; Nikolay I. Chervyakov; Pavel Alekseevich Lyakhov; Andrey S. Ionisyan; Maria V. Valueva; Vyacheslav V. Gulvanskiy; Rangababu Peesapati (TSP, 2019)

High-Performance Hardware 3D Medical Imaging using Wavelets in the Residue Number System. - Nikolay I. Chervyakov; Pavel Alekseevich Lyakhov; Nikolay N. Nagornov; Maria V. Valueva; Dmitrii I. Kaplun (MECO, 2020)

Method of Oriented Contour Detection on Image Using Lorentz Function. - Pavel Alekseevich Lyakhov; Albina S. Abdulsalyamova; Maria R. Kiladze; Dmitrii I. Kaplun; Alexander S. Voznesensky (MECO, 2020)

Method for Determining Skin Lesions from Images Using Neural Network. - Uliana A. Lyakhova; Pavel Alekseevich Lyakhov; Nikolay I. Chervyakov; Dmitrii I. Kaplun; Alexander S. Voznesensky (MECO, 2020)

Classification of Moduli Sets for Residue Number System With Special Diagonal Functions. - Peter G. Boyvalenkov; Nikolay I. Chervyakov; Pavel Alekseevich Lyakhov; Nataliya Semyonova; Anton S. Nazarov; Maria V. Valueva; Georgi Boyvalenkov; Danil Bogaevskiy; Dmitry I. Kaplun (IEEE Access, 2020)

High-Performance Digital Filtering on Truncated Multiply-Accumulate Units in the Residue Number System. - Pavel Alekseevich Lyakhov; Maria V. Valueva; Georgii V. Valuev; Nikolay N. Nagornov (IEEE Access, 2020)

Residue Number System-Based Solution for Reducing the Hardware Cost of a Convolutional Neural Network. - Nikolay I. Chervyakov; Pavel Alekseevich Lyakhov; Maxim Anatolievich Deryabin; N. N. Nagornov; Maria V. Valueva; Georgii V. Valuev (Neurocomputing, 2020)

Application of the residue number system to reduce hardware costs of the convolutional neural network implementation. - Maria V. Valueva; N. N. Nagornov; Pavel Alekseevich Lyakhov; Georgii V. Valuev; Nikolay I. Chervyakov (Math. Comput. Simul., 2020)

Design Reverse Converter for Balanced RNS with Three Low-cost Modules. - Pavel Alekseevich Lyakhov; Maxim V. Bergerman; Nataliya Semyonova; Dmitrij I. Kaplun; Alexander S. Voznesensky (MECO, 2021)

A New Method of Sign Detection in RNS Based on Modified Chinese Remainder Theorem. - Pavel Alekseevich Lyakhov; Maria V. Valueva; Dmitry I. Kaplun; Alexander S. Voznesensky (MECO, 2021)

Single Image Super-Resolution Method Based on Bilinear Interpolation and U-Net Combination. - Pavel Alekseevich Lyakhov; Georgii V. Valuev; Maria V. Valueva; Dmitry I. Kaplun; Aleksandr Sinitca (MECO, 2021)

Digital Filter Architecture With Calculations in the Residue Number System by Winograd Method F (2 × 2, 2 × 2). - Maria V. Valueva; Pavel Alekseevich Lyakhov; Georgii V. Valuev; Nikolay N. Nagornov (IEEE Access, 2021)

On the Computational Complexity of 2D Filtering by Winograd Method. - Pavel Alekseevich Lyakhov; Albina S. Abdulsalyamova; Nataliya Semyonova; Nikolay N. Nagornov; Alexander S. Voznesensky; Dmitrii I. Kaplun (MECO, 2022)

Efficient Probabilistic Filtering of Data Subject to Channel Noise Under Local Pooling Conditions. - Pavel Alekseevich Lyakhov; Diana I. Kalita; Aleksandr M. Sinitca; Alexander S. Voznesensky (MECO, 2022)

Bilateral and Median Filter Combination for High-Quality Cleaning of Random Impulse Noise in Images. - Pavel Alekseevich Lyakhov; Alexander S. Voznesensky; Evgeniy D. Shalugin; Anzor R. Orazaev; Valentina A. Baboshina (MECO, 2022)

RNS-Based FPGA Accelerators for High-Quality 3D Medical Image Wavelet Processing Using Scaled Filter Coefficients. - Nikolay N. Nagornov; Pavel Alekseevich Lyakhov; Maria V. Valueva; Maxim V. Bergerman (IEEE Access, 2022)

Moving Object Detection Based on a Combination of Kalman Filter and Median Filtering. - Diana I. Kalita; Pavel Alekseevich Lyakhov (Big Data Cogn. Comput., 2022)

Neural network system for analyzing statistical factors of patients for predicting the survival of dental implants. - Pavel Alekseevich Lyakhov; Alexander Alexandrovich Dolgalev; Uliana A. Lyakhova; Alexandr Alexandrovich Muraev; Kirill Evgenievich Zolotayev; Dmitry Yurievich Semerikov (Frontiers Neuroinformatics, 2022)

High Performance Parallel Pseudorandom Number Generator on Cellular Automata. - Alla Levina; Daniyar Mukhamedjanov; Danil Bogaevskiy; Pavel Alekseevich Lyakhov; Maria V. Valueva; Dmitrii I. Kaplun (Symmetry, 2022)

Multimodal Neural Network for Recognition of Cardiac Arrhythmias Based on 12-Load Electrocardiogram Signals. - Maria R. Kiladze; Ulyana A. Lyakhova; Pavel A. Lyakhov; Nikolay N. Nagornov; Mohsen Vahabi (IEEE Access, 2023)

Multimodal Analysis of Unbalanced Dermatological Data for Skin Cancer Recognition. - Pavel A. Lyakhov; Ulyana A. Lyakhova; Diana I. Kalita (IEEE Access, 2023)

A novel sign detection method in residue number system based on Chinese remainder theorem with fractional values. - Pavel A. Lyakhov; Maxim V. Bergerman; Ruslan Abdulkadirov; Albina S. Abdulsalyamova; Nikolay N. Nagornov; Alexander S. Voznesenskiy; Dmitrii V. Minenkov; Dmitrii I. Kaplun (Microprocess. Microsystems, 2023)

A novel QCA circuit-switched network with power dissipation analysis for nano communication applications. - Mohsen Vahabi; Ehsan Rahimi; Pavel A. Lyakhov; Akira Otsuki (Nano Commun. Networks, 2023)

Reliable Kalman Filtering with Conditionally Local Calculations in Wireless Sensor Networks. - Pavel A. Lyakhov; Diana I. Kalita (Autom. Control. Comput. Sci., 2023)

Area-Efficient digital filtering based on truncated multiply-accumulate units in residue number system 2n-1,2n,2n+1. - Pavel A. Lyakhov (J. King Saud Univ. Comput. Inf. Sci., 2023)

Residue number systems with six modules and efficient circuits based on power-of-two diagonal modulus. - Peter G. Boyvalenkov; Pavel A. Lyakhov; Nataliya Semyonova; Maria V. Valueva; Georgi Boyvalenkov; Dmitrii V. Minenkov; Dmitrii I. Kaplun (Comput. Electr. Eng., 2023)

Improving the Accuracy of Neural Network Pattern Recognition by Fractional Gradient Descent. - Ruslan Abdulkadirov; Pavel A. Lyakhov; Valentina A. Baboshina; Nikolay N. Nagornov (IEEE Access, 2024)

Modern Trends in Improving the Technical Characteristics of Devices and Systems for Digital Image Processing. - Nikolay N. Nagornov; Pavel A. Lyakhov; Maxim V. Bergerman; Diana I. Kalita (IEEE Access, 2024)

Systematic review of approaches to detection and classification of skin cancer using artificial intelligence: Development and prospects. - Uliana A. Lyakhova; Pavel A. Lyakhov (Comput. Biol. Medicine, 2024)

Efficient design and implementation of a reversible switched network in quantum cellular automata technology. - Mohsen Vahabi; Ehsan Rahimi; Pavel A. Lyakhov (J. King Saud Univ. Comput. Inf. Sci., 2024)