| DC Field | Value | Language |
|---|
| dc.contributor.author | Leonov, I. | - |
| dc.coverage.spatial | Минск | en_US |
| dc.date.accessioned | 2024-02-16T06:30:27Z | - |
| dc.date.available | 2024-02-16T06:30:27Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.citation | Leonov, I. Performance Analysis for Sequential Statistical Discrimination of Gaussian Random Fields / I. Leonov // Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023) : Proceedings of the 16th International Conference, October 17–19, 2023, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2023. – P. 212–214. | en_US |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/54282 | - |
| dc.description.abstract | Stochastic processes stand as a versatile tool for modeling and understanding random phenomena. These
processes describe system evolution while taking into account randomness and uncertainty. Nowadays, stochastic processes find application in a variety of domains, such as modeling financial markets, monitoring manufacturing procedures and predicting disease spread. This paper proposes a sequential procedure for testing hypotheses concerning the correlational structure of random fields and their trends. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | BSU | en_US |
| dc.subject | материалы конференций | en_US |
| dc.subject | random field | en_US |
| dc.subject | sequential decision rule | en_US |
| dc.subject | Gaussian random field | en_US |
| dc.subject | sequential analysis | en_US |
| dc.title | Performance Analysis for Sequential Statistical Discrimination of Gaussian Random Fields | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023)
|
