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The Use of Artificial Neural Networks for Classification of Signal Sources in Cognitive Radio Systemsстатья
Информация о цитировании статьи получена из
Web of Science,
Scopus
Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 19 июля 2016 г.
- Авторы: Adjemov S.S., Klenov N.V., Tereshonok M.V., Chirov D.S.
- Журнал: Programming and Computer Software
- Том: 42
- Номер: 3
- Год издания: 2016
- Издательство: Pleiades Publishing, Ltd
- Местоположение издательства: Road Town, United Kingdom
- Первая страница: 121
- Последняя страница: 128
- DOI: 10.1134/S0361768816030026
- Аннотация: In the paper, methods of classification of signal sources in cognitive radio systems that are based on artificial neural networks are discussed. A novel method for improving noise immunity of RBF networks is suggested. It is based on introducing an additional self-organizing layer of neurons, which ensures automatic selection of variances of basis functions and a significant reduction of the network dimension. It is shown that the use of auto-associative networks in the problem of the classification of sources of signals makes it possible to minimize the feature space without significant deterioration of its separation properties
- Добавил в систему: Кленов Николай Викторович