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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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Games with incomplete information on both sides and with a public signal on the state of the game

P. 68–78.
Gavrilovich M., Kreps V. L.
In press

Supposing that Player 1’s computational power is higher than that of Player 2, we give three examples of different kinds of public signal about the state of a two-person zero-sum game with symmetric incom- plete information on both sides (both players do not know the state of the game) where Player 1 due to his computational power learns the state of the game meanwhile it is impossible for Player 2. That is, the game with incomplete information on both sides becomes a game with incomplete information on the side of Player 2. Thus we demonstrate that information about the state of a game may appear not only due to a private signal but as a result of a public signal and asymmetric computational resources of players.

Language: English
Full text
Text on another site
Keywords: asymmetryzero-sum gamesfinite automata incomplete information
Publication based on the results of:
­­­Axiomatic aspects of fair division problems (2017)

In book

Contributions to Game Theory and Management
Vol. 10. , St. Petersburg: Graduate School of Management SPbU, 2017.
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