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Design of order statistics filters using feedforward neural networks

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dc.contributor.author Maslennikova Y.
dc.contributor.author Bochkarev V.
dc.date.accessioned 2018-09-19T21:35:56Z
dc.date.available 2018-09-19T21:35:56Z
dc.date.issued 2016
dc.identifier.issn 1742-6588
dc.identifier.uri https://dspace.kpfu.ru/xmlui/handle/net/144183
dc.description.abstract © Published under licence by IOP Publishing Ltd.In recent years significant progress have been made in the development of nonlinear data processing techniques. Such techniques are widely used in digital data filtering and image enhancement. Many of the most effective nonlinear filters based on order statistics. The widely used median filter is the best known order statistic filter. Generalized form of these filters could be presented based on Lloyd's statistics. Filters based on order statistics have excellent robustness properties in the presence of impulsive noise. In this paper, we present special approach for synthesis of order statistics filters using artificial neural networks. Optimal Lloyd's statistics are used for selecting of initial weights for the neural network. Adaptive properties of neural networks provide opportunities to optimize order statistics filters for data with asymmetric distribution function. Different examples demonstrate the properties and performance of presented approach.
dc.relation.ispartofseries Journal of Physics: Conference Series
dc.title Design of order statistics filters using feedforward neural networks
dc.type Conference Paper
dc.relation.ispartofseries-issue 1
dc.relation.ispartofseries-volume 738
dc.collection Публикации сотрудников КФУ
dc.source.id SCOPUS17426588-2016-738-1-SID84988693382


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  • Публикации сотрудников КФУ Scopus [24551]
    Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.

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