Please use this identifier to cite or link to this item: https://elib.psu.by/handle/123456789/48757
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dc.contributor.authorBohush, R.-
dc.contributor.authorAdamovskiy, Y.-
dc.contributor.authorNaumovich, N.-
dc.date.accessioned2025-12-01T12:21:22Z-
dc.date.available2025-12-01T12:21:22Z-
dc.date.issued2025-
dc.identifier.citationBohush, R., Adamovskiy, Y., Naumovich, N. (2025). Comparing LSTM and KAN Models for Predicting Channel Resource Occupancy in Cognitive Radio. In: Wang, L., Gao, L., Lu, X. (eds) Innovations in Images, Signals, and Computing. ICISC 2024. Lecture Notes in Networks and Systems, vol 1411. Springer, Cham. https://doi.org/10.1007/978-3-031-91683-0_9ru_RU
dc.identifier.urihttps://elib.psu.by/handle/123456789/48757-
dc.language.isoenru_RU
dc.publisherSpringer Natureru_RU
dc.titleComparing LSTM and KAN Models for Predicting Channel Resource Occupancy in Cognitive Radioru_RU
dc.typeArticleru_RU
dc.identifier.doi10.1007/978-3-031-91683-0_9-
Appears in Collections:Машинное обучение. Обработкой изображений и видео. Интеллектуальные системы. Информационная безопасность
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