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ORCIDPavel A. Lyakhov
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2020 – today
- 2024
[j27]Nikolay N. Nagornov
, Pavel A. Lyakhov, Maxim V. Bergerman, Diana I. Kalita:
Modern Trends in Improving the Technical Characteristics of Devices and Systems for Digital Image Processing. IEEE Access 12: 44659-44681 (2024)- [j26]Ruslan Abdulkadirov, Pavel A. Lyakhov, Valentina A. Baboshina, Nikolay N. Nagornov:
Improving the Accuracy of Neural Network Pattern Recognition by Fractional Gradient Descent. IEEE Access 12: 168428-168444 (2024) - [j25]Uliana A. Lyakhova, Pavel A. Lyakhov:
Systematic review of approaches to detection and classification of skin cancer using artificial intelligence: Development and prospects. Comput. Biol. Medicine 178: 108742 (2024) - [j24]Mohsen Vahabi, Ehsan Rahimi, Pavel A. Lyakhov:
Efficient design and implementation of a reversible switched network in quantum cellular automata technology. J. King Saud Univ. Comput. Inf. Sci. 36(1): 101910 (2024) - 2023
- [j23]Pavel A. Lyakhov, Ulyana A. Lyakhova, Diana I. Kalita:
Multimodal Analysis of Unbalanced Dermatological Data for Skin Cancer Recognition. IEEE Access 11: 131487-131507 (2023) - [j22]Maria R. Kiladze, Ulyana A. Lyakhova, Pavel A. Lyakhov, Nikolay N. Nagornov, Mohsen Vahabi:
Multimodal Neural Network for Recognition of Cardiac Arrhythmias Based on 12-Load Electrocardiogram Signals. IEEE Access 11: 133744-133754 (2023) - [j21]Pavel A. Lyakhov, Diana I. Kalita:
Reliable Kalman Filtering with Conditionally Local Calculations in Wireless Sensor Networks. Autom. Control. Comput. Sci. 57(2): 154-166 (2023) - [j20]Peter G. Boyvalenkov, Pavel A. Lyakhov, Nataliya Semyonova, Maria V. Valueva, Georgi Boyvalenkov, Dmitrii V. Minenkov, Dmitrii I. Kaplun:
Residue number systems with six modules and efficient circuits based on power-of-two diagonal modulus. Comput. Electr. Eng. 110: 108854 (2023) - [j19]Pavel A. Lyakhov:
Area-Efficient digital filtering based on truncated multiply-accumulate units in residue number system 2n-1,2n,2n+1. J. King Saud Univ. Comput. Inf. Sci. 35(6): 101574 (2023) - [j18]Pavel A. Lyakhov, Maxim V. Bergerman, Ruslan Abdulkadirov, Albina S. Abdulsalyamova, Nikolay N. Nagornov, Alexander S. Voznesenskiy, Dmitrii V. Minenkov, Dmitrii I. Kaplun:
A novel sign detection method in residue number system based on Chinese remainder theorem with fractional values. Microprocess. Microsystems 102: 104940 (2023) - [j17]Mohsen Vahabi, Ehsan Rahimi, Pavel A. Lyakhov, Akira Otsuki:
A novel QCA circuit-switched network with power dissipation analysis for nano communication applications. Nano Commun. Networks 35: 100438 (2023) - 2022
- [j16]Nikolay N. Nagornov, Pavel Alekseevich Lyakhov, Maria V. Valueva, Maxim V. Bergerman:
RNS-Based FPGA Accelerators for High-Quality 3D Medical Image Wavelet Processing Using Scaled Filter Coefficients. IEEE Access 10: 19215-19231 (2022) - [j15]Diana I. Kalita, Pavel Alekseevich Lyakhov:
Moving Object Detection Based on a Combination of Kalman Filter and Median Filtering. Big Data Cogn. Comput. 6(4): 142 (2022) - [j14]Pavel Alekseevich Lyakhov, Alexander Alexandrovich Dolgalev, Uliana A. Lyakhova, Alexandr Alexandrovich Muraev, Kirill Evgenievich Zolotayev, Dmitry Yurievich Semerikov:
Neural network system for analyzing statistical factors of patients for predicting the survival of dental implants. Frontiers Neuroinformatics 16 (2022) - [j13]Alla Levina, Daniyar Mukhamedjanov, Danil Bogaevskiy, Pavel Alekseevich Lyakhov, Maria V. Valueva, Dmitrii I. Kaplun:
High Performance Parallel Pseudorandom Number Generator on Cellular Automata. Symmetry 14(9): 1869 (2022) - [c13]Pavel Alekseevich Lyakhov, Albina S. Abdulsalyamova, Nataliya Semyonova, Nikolay N. Nagornov, Alexander S. Voznesensky, Dmitrii I. Kaplun:
On the Computational Complexity of 2D Filtering by Winograd Method. MECO 2022: 1-4 - [c12]Pavel Alekseevich Lyakhov, Diana I. Kalita, Aleksandr M. Sinitca, Alexander S. Voznesensky:
Efficient Probabilistic Filtering of Data Subject to Channel Noise Under Local Pooling Conditions. MECO 2022: 1-5 - [c11]Pavel Alekseevich Lyakhov, Alexander S. Voznesensky, Evgeniy D. Shalugin, Anzor R. Orazaev, Valentina A. Baboshina:
Bilateral and Median Filter Combination for High-Quality Cleaning of Random Impulse Noise in Images. MECO 2022: 1-5 - 2021
- [j12]Maria V. Valueva, Pavel Alekseevich Lyakhov, Georgii V. Valuev, Nikolay N. Nagornov:
Digital Filter Architecture With Calculations in the Residue Number System by Winograd Method F (2 × 2, 2 × 2). IEEE Access 9: 143331-143340 (2021) - [c10]Pavel Alekseevich Lyakhov, Maxim V. Bergerman, Nataliya Semyonova, Dmitrij Kaplun, Alexander S. Voznesensky:
Design Reverse Converter for Balanced RNS with Three Low-cost Modules. MECO 2021: 1-7 - [c9]Pavel Alekseevich Lyakhov, Maria V. Valueva, Dmitry I. Kaplun, Alexander S. Voznesensky:
A New Method of Sign Detection in RNS Based on Modified Chinese Remainder Theorem. MECO 2021: 1-4 - [c8]Pavel Alekseevich Lyakhov, Georgii V. Valuev, Maria V. Valueva, Dmitry I. Kaplun, Aleksandr Sinitca:
Single Image Super-Resolution Method Based on Bilinear Interpolation and U-Net Combination. MECO 2021: 1-4 - 2020
- [j11]Peter G. Boyvalenkov, Nikolay I. Chervyakov, Pavel Alekseevich Lyakhov, Nataliya Semyonova, Anton S. Nazarov, Maria V. Valueva, Georgi Boyvalenkov, Danil Bogaevskiy, Dmitry I. Kaplun:
Classification of Moduli Sets for Residue Number System With Special Diagonal Functions. IEEE Access 8: 156104-156116 (2020) - [j10]Pavel Alekseevich Lyakhov, Maria V. Valueva, Georgii V. Valuev, Nikolay N. Nagornov:
High-Performance Digital Filtering on Truncated Multiply-Accumulate Units in the Residue Number System. IEEE Access 8: 209181-209190 (2020) - [j9]Nikolay I. Chervyakov, Pavel Alekseevich Lyakhov, Maxim Anatolievich Deryabin, N. N. Nagornov, Maria V. Valueva, Georgii V. Valuev:
Residue Number System-Based Solution for Reducing the Hardware Cost of a Convolutional Neural Network. Neurocomputing 407: 439-453 (2020) - [j8]Maria V. Valueva, N. N. Nagornov, Pavel Alekseevich Lyakhov, Georgii V. Valuev, Nikolay I. Chervyakov:
Application of the residue number system to reduce hardware costs of the convolutional neural network implementation. Math. Comput. Simul. 177: 232-243 (2020) - [c7]Nikolay I. Chervyakov, Pavel Alekseevich Lyakhov, Nikolay N. Nagornov, Maria V. Valueva, Dmitrii I. Kaplun:
High-Performance Hardware 3D Medical Imaging using Wavelets in the Residue Number System. MECO 2020: 1-4 - [c6]Pavel Alekseevich Lyakhov, Albina S. Abdulsalyamova, Maria R. Kiladze, Dmitrii I. Kaplun, Alexander S. Voznesensky:
Method of Oriented Contour Detection on Image Using Lorentz Function. MECO 2020: 1-4 - [c5]Uliana A. Lyakhova, Pavel Alekseevich Lyakhov, Nikolay I. Chervyakov, Dmitrii I. Kaplun, Alexander S. Voznesensky:
Method for Determining Skin Lesions from Images Using Neural Network. MECO 2020: 1-4
2010 – 2019
- 2019
- [c4]Nikolay I. Chervyakov, Pavel Alekseevich Lyakhov, Nikolay N. Nagornov, Dmitrii I. Kaplun, Alexander S. Voznesenskiy, Danil V. Bogayevskiy:
Implementation of Smoothing Image Filtering in the Residue Number System. MECO 2019: 1-4 - [c3]Dmitrii I. Kaplun, Nikolay I. Chervyakov, Pavel Alekseevich Lyakhov, Andrey S. Ionisyan, Maria V. Valueva, Vyacheslav V. Gulvanskiy, Rangababu Peesapati:
Hardware Implementation of Video Processing Device using Residue Number System. TSP 2019: 701-704 - 2018
- [j7]Héctor Pettenghi, Rogerio Paludo, Roberto de Matos, Pavel Alekseevich Lyakhov:
Efficient RNS Reverse Converters for Moduli Sets with Dynamic Ranges Up to \((10n+1)\) -bit. Circuits Syst. Signal Process. 37(11): 5178-5196 (2018) - [j6]Nikolay I. Chervyakov, Pavel Alekseevich Lyakhov, Mikhail G. Babenko, Irina N. Lavrinenko, Anton V. Lavrinenko, Anton S. Nazarov:
The architecture of a fault-tolerant modular neurocomputer based on modular number projections. Neurocomputing 272: 96-107 (2018) - [j5]Nikolay I. Chervyakov, Pavel Alekseevich Lyakhov, Mikhail G. Babenko, Irina N. Lavrinenko, Anton V. Lavrinenko, Maxim Anatolievich Deryabin, Anton S. Nazarov:
A new model to optimize the architecture of a fault-tolerant modular neurocomputer. Neurocomputing 303: 37-46 (2018) - [c2]Nikolay I. Chervyakov, Pavel Alekseevich Lyakhov, Maria V. Valueva, Georgii V. Valuev, Dmitrii I. Kaplun, George A. Efimenko, Denis V. Gnezdilov:
Area-Efficient FPGA Implementation of Minimalistic Convolutional Neural Network Using Residue Number System. FRUCT 2018: 112-118 - 2017
- [j4]Nikolay I. Chervyakov, Amir Sabbagh Molahosseini, Pavel Alekseevich Lyakhov, Mikhail G. Babenko, Maxim Anatolievich Deryabin:
Residue-to-binary conversion for general moduli sets based on approximate Chinese remainder theorem. Int. J. Comput. Math. 94(9): 1833-1849 (2017) - [c1]Roberto de Matos, Rogerio Paludo, Nikolay I. Chervyakov, Pavel Alekseevich Lyakhov, Héctor Pettenghi:
Efficient implementation of modular multiplication by constants applied to RNS reverse converters. ISCAS 2017: 1-4 - 2016
- [j3]Nikolay I. Chervyakov, Pavel Alekseevich Lyakhov, Mikhail G. Babenko, A. I. Garyanina, Irina N. Lavrinenko, Anton V. Lavrinenko, Maxim Anatolievich Deryabin:
An efficient method of error correction in fault-tolerant modular neurocomputers. Neurocomputing 205: 32-44 (2016) - 2015
- [j2]Nikolay I. Chervyakov, Amir Sabbagh Molahosseini, Pavel Alekseevich Lyakhov, Mikhail G. Babenko, Irina N. Lavrinenko, Anton V. Lavrinenko:
Comparison of modular numbers based on the chinese remainder theorem with fractional values. Autom. Control. Comput. Sci. 49(6): 354-365 (2015) - 2014
- [j1]Nikolay I. Chervyakov, Pavel Alekseevich Lyakhov, Mikhail G. Babenko:
Digital filtering of images in a residue number system using finite-field wavelets. Autom. Control. Comput. Sci. 48(3): 180-189 (2014)
Coauthor Index
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