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May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
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A Brief Overview and Experimental Researches of Novel PL-log-MAP Turbo Decoding Algorithm

Ch. 1. P. 1–6.
Stukach O., Romanyuk A. N., Ivanov Y. Y.

In the paper, we will discuss the powerfull class of channel codes referred to as turbo codes. We commence with a brief discussion for MAP and log-MAP decoding algorithms. Then we work with proposed turbo decoding method, which is called as PL-log-MAP. Some numerical results and research experiments, such as simulation for bit error rate estimation and images transmission have been presented. It is shown that PL-log-MAP algorithm performance is almost the same as for original log-MAP. So, this algorithm can be used in digital communication systems

Language: English
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Keywords: кодированиеblock code

In book

2017 International Siberian Conference on Control and Communications (SIBCON)
2017 International Siberian Conference on Control and Communications (SIBCON)
IEEE, 2017.
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