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Selection and Recognition of Statistically Defined Signals in Learning Systems

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Standard

Selection and Recognition of Statistically Defined Signals in Learning Systems. / Bezruk, Valeriy ; Omelchenko, Anatolii ; Fedorov, Oleksii et al.
IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society: Proceedings. Piscataway: IEEE - Institute of Electrical and Electronics Engineers Inc., 2018. p. 3211-3216 8591321 (Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Harvard

Bezruk, V, Omelchenko, A, Fedorov, O, Mercorelli, P & Nieto Hipólito, JI 2018, Selection and Recognition of Statistically Defined Signals in Learning Systems. in IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society: Proceedings., 8591321, Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society, IEEE - Institute of Electrical and Electronics Engineers Inc., Piscataway, pp. 3211-3216. https://doi.org/10.1109/IECON.2018.8591321

APA

Bezruk, V., Omelchenko, A., Fedorov, O., Mercorelli, P., & Nieto Hipólito, J. I. (2018). Selection and Recognition of Statistically Defined Signals in Learning Systems. In IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society: Proceedings (pp. 3211-3216). Article 8591321 (Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society). IEEE - Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IECON.2018.8591321

Vancouver

Bezruk V, Omelchenko A, Fedorov O, Mercorelli P, Nieto Hipólito JI. Selection and Recognition of Statistically Defined Signals in Learning Systems. In IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society: Proceedings. Piscataway: IEEE - Institute of Electrical and Electronics Engineers Inc. 2018. p. 3211-3216. 8591321. (Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society). doi: 10.1109/IECON.2018.8591321

Bibtex

@inbook{1dbd3acbe405454bbe0c064e98a8a070,
title = "Selection and Recognition of Statistically Defined Signals in Learning Systems",
abstract = "The paper addresses a non-traditional problem of pattern recognition, when information about pattern is represented in the form of a random signal taken from the output of a corresponding physical sensor. It is supposed that there exist two types of signal to recognize, namely, specified in the statistical sense signals and totally unknown signals. Such the conditions are called conditions of increased a priory uncertainty. Developing a technique to recognize specified signals in conditions of increased a priory uncertainty is the objective of this paper. Methods for selection and recognition of a statistically defined random signal are proposed for the cases when signal description is done by various probabilistic models. Additional consideration is given to peculiarities of employing these methods for solving applied problems of pattern recognition in radar, medical diagnostics and speaker identification.",
keywords = "Engineering, radio location, pattern recognition, random signal, probalistic model, decision rule",
author = "Valeriy Bezruk and Anatolii Omelchenko and Oleksii Fedorov and Paolo Mercorelli and {Nieto Hip{\'o}lito}, {Juan Ivan}",
year = "2018",
month = dec,
day = "26",
doi = "10.1109/IECON.2018.8591321",
language = "English",
isbn = "978-1-5090-6685-8",
series = "Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society",
publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",
pages = "3211--3216",
booktitle = "IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society",
address = "United States",

}

RIS

TY - CHAP

T1 - Selection and Recognition of Statistically Defined Signals in Learning Systems

AU - Bezruk, Valeriy

AU - Omelchenko, Anatolii

AU - Fedorov, Oleksii

AU - Mercorelli, Paolo

AU - Nieto Hipólito, Juan Ivan

PY - 2018/12/26

Y1 - 2018/12/26

N2 - The paper addresses a non-traditional problem of pattern recognition, when information about pattern is represented in the form of a random signal taken from the output of a corresponding physical sensor. It is supposed that there exist two types of signal to recognize, namely, specified in the statistical sense signals and totally unknown signals. Such the conditions are called conditions of increased a priory uncertainty. Developing a technique to recognize specified signals in conditions of increased a priory uncertainty is the objective of this paper. Methods for selection and recognition of a statistically defined random signal are proposed for the cases when signal description is done by various probabilistic models. Additional consideration is given to peculiarities of employing these methods for solving applied problems of pattern recognition in radar, medical diagnostics and speaker identification.

AB - The paper addresses a non-traditional problem of pattern recognition, when information about pattern is represented in the form of a random signal taken from the output of a corresponding physical sensor. It is supposed that there exist two types of signal to recognize, namely, specified in the statistical sense signals and totally unknown signals. Such the conditions are called conditions of increased a priory uncertainty. Developing a technique to recognize specified signals in conditions of increased a priory uncertainty is the objective of this paper. Methods for selection and recognition of a statistically defined random signal are proposed for the cases when signal description is done by various probabilistic models. Additional consideration is given to peculiarities of employing these methods for solving applied problems of pattern recognition in radar, medical diagnostics and speaker identification.

KW - Engineering

KW - radio location

KW - pattern recognition

KW - random signal

KW - probalistic model

KW - decision rule

UR - http://www.scopus.com/inward/record.url?scp=85061549311&partnerID=8YFLogxK

U2 - 10.1109/IECON.2018.8591321

DO - 10.1109/IECON.2018.8591321

M3 - Article in conference proceedings

SN - 978-1-5090-6685-8

T3 - Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society

SP - 3211

EP - 3216

BT - IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

CY - Piscataway

ER -

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Fernandes, F. M., Dos Santos, M. F., De Morais, M. H. F., Lima, J., Pereira, A. I. & Mercorelli, P., 2025, Proceedings of the 2025 26th International Carpathian Control Conference (ICCC): Grandhotel Starý Smokovec, High Tatras, Starý Smokovec, Slovak Republic, 19-21 May 2025. Kacur, J., Skovranek, T., Laciak, M. & Mojzisova, A. (eds.). Piscataway: Institute of Electrical and Electronics Engineers Inc., 6 p. (International Carpathian Control Conference, ICCC; vol. 26).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

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Research output: Journal contributions › Journal articles › Research › peer-review

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Research output: Journal contributions › Journal articles › Research › peer-review

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Research output: Journal contributions › Journal articles › Research › peer-review

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Research output: Journal contributions › Journal articles › Research › peer-review

DOI

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