eONPUIR

Diagnostic features space construction using Volterra kernels wavelet transforms

Показать сокращенную информацию

dc.contributor.author Medvedew, Andrey
dc.contributor.author Fomin, Oleksandr
dc.contributor.author Pavlenko, Vitaliy
dc.contributor.author Speranskyy, Viktor
dc.contributor.author Медведєв, Андрій
dc.contributor.author Фомін, Олександр Олексійович
dc.contributor.author Павленко, Віталій Данилович
dc.contributor.author Сперанський, Віктор Олександрович
dc.date.accessioned 2022-09-30T10:47:02Z
dc.date.available 2022-09-30T10:47:02Z
dc.date.issued 2017
dc.identifier.citation Medvedew, Andrey. Diagnostic features space construction using Volterra kernels wavelet transforms / Andrey Medvedew; Oleksandr Fomin; Vitaliy Pavlenko; Viktor Speranskyy // Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). - 2017, Vol. 2. - P. 1077 - 1081. en
dc.identifier.issn https://www.researchgate.net/publication/321353242_Diagnostic_features_space_construction_using_Volterra_kernels_wavelet_transforms
dc.identifier.uri 10.1109/IDAACS.2017.8095251
dc.identifier.uri http://ieeexplore.ieee.org/document/8095251/
dc.identifier.uri http://dspace.opu.ua/jspui/handle/123456789/13009
dc.description.abstract Abstract—In this paper the problem of improving the reliability of nonlinear dynamic objects fault diagnosing is presented. Model-based diagnostics nonparametric identification method is used. Diagnostic models are constructed on the base of Volterra kernels wavelet transforms. The effectiveness of the suggested diagnostic models based on Volterra kernels wavelet transforms is analyzed on the basis of simulation model of nonlinear dynamic object. en
dc.language.iso en_US en
dc.publisher IEEE en
dc.subject Volterra kernels en
dc.subject diagnostics efficiency en
dc.subject fault diagnosis en
dc.subject wavelet transform en
dc.subject feature space reduction en
dc.title Diagnostic features space construction using Volterra kernels wavelet transforms en
dc.type Article in Scopus en
opu.kafedra Кафедра комп’ютеризовані системи та програмні технології
opu.citation.volume Vol. 2 en
opu.citation.firstpage 1077 en
opu.citation.lastpage 1081 en
opu.citation.conference 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) en
opu.staff.id speranskyy@op.edu.ua en
opu.staff.id pavlenko@opu.ua en
opu.staff.id fomin@op.edu.ua en
opu.conference.dates 21-23 Sept. 2017 en


Файлы, содержащиеся в элементе

Этот элемент содержится в следующих коллекциях

Показать сокращенную информацию