Correlation method for pattern recognition

A new approach towards solving the pattern recognition problems in hybrid optical/digital correlators is suggested. The method is based on the authors' know-how-principle of transforming the field intensity or amplitude data on the identified object assuming that these data may be entered into...

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Бібліографічні деталі
Опубліковано в: :Semiconductor Physics Quantum Electronics & Optoelectronics
Дата:2002
Автори: Yezhov, P.V., Kuzmenko, A.V., Komarov, V.A.
Формат: Стаття
Мова:English
Опубліковано: Інститут фізики напівпровідників імені В.Є. Лашкарьова НАН України 2002
Онлайн доступ:https://nasplib.isofts.kiev.ua/handle/123456789/121354
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Назва журналу:Digital Library of Periodicals of National Academy of Sciences of Ukraine
Цитувати:Correlation method for pattern recognition / P.V. Yezhov, A.V. Kuzmenko, V.A. Komarov // Semiconductor Physics Quantum Electronics & Optoelectronics. — 2002. — Т. 5, № 4. — С. 431-433. — Бібліогр.: 3 назв. — англ.

Репозитарії

Digital Library of Periodicals of National Academy of Sciences of Ukraine
id nasplib_isofts_kiev_ua-123456789-121354
record_format dspace
spelling Yezhov, P.V.
Kuzmenko, A.V.
Komarov, V.A.
2017-06-14T07:48:53Z
2017-06-14T07:48:53Z
2002
Correlation method for pattern recognition / P.V. Yezhov, A.V. Kuzmenko, V.A. Komarov // Semiconductor Physics Quantum Electronics & Optoelectronics. — 2002. — Т. 5, № 4. — С. 431-433. — Бібліогр.: 3 назв. — англ.
1560-8034
PACS: 42.30.Sy, 42.30.Wb, 42.79.Hp
https://nasplib.isofts.kiev.ua/handle/123456789/121354
A new approach towards solving the pattern recognition problems in hybrid optical/digital correlators is suggested. The method is based on the authors' know-how-principle of transforming the field intensity or amplitude data on the identified object assuming that these data may be entered into a computer by ordinary methods. This principle allows to solve the unification of the correlation functions and recognition attributes selection problem using a unified, identified object's class-independent method. Presented experimental results confirm applicability of this approach.
en
Інститут фізики напівпровідників імені В.Є. Лашкарьова НАН України
Semiconductor Physics Quantum Electronics & Optoelectronics
Correlation method for pattern recognition
Article
published earlier
institution Digital Library of Periodicals of National Academy of Sciences of Ukraine
collection DSpace DC
title Correlation method for pattern recognition
spellingShingle Correlation method for pattern recognition
Yezhov, P.V.
Kuzmenko, A.V.
Komarov, V.A.
title_short Correlation method for pattern recognition
title_full Correlation method for pattern recognition
title_fullStr Correlation method for pattern recognition
title_full_unstemmed Correlation method for pattern recognition
title_sort correlation method for pattern recognition
author Yezhov, P.V.
Kuzmenko, A.V.
Komarov, V.A.
author_facet Yezhov, P.V.
Kuzmenko, A.V.
Komarov, V.A.
publishDate 2002
language English
container_title Semiconductor Physics Quantum Electronics & Optoelectronics
publisher Інститут фізики напівпровідників імені В.Є. Лашкарьова НАН України
format Article
description A new approach towards solving the pattern recognition problems in hybrid optical/digital correlators is suggested. The method is based on the authors' know-how-principle of transforming the field intensity or amplitude data on the identified object assuming that these data may be entered into a computer by ordinary methods. This principle allows to solve the unification of the correlation functions and recognition attributes selection problem using a unified, identified object's class-independent method. Presented experimental results confirm applicability of this approach.
issn 1560-8034
url https://nasplib.isofts.kiev.ua/handle/123456789/121354
citation_txt Correlation method for pattern recognition / P.V. Yezhov, A.V. Kuzmenko, V.A. Komarov // Semiconductor Physics Quantum Electronics & Optoelectronics. — 2002. — Т. 5, № 4. — С. 431-433. — Бібліогр.: 3 назв. — англ.
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first_indexed 2025-11-28T07:30:38Z
last_indexed 2025-11-28T07:30:38Z
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