title: Ð Ð°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ðµ ÑÐ¸Ð¿Ð° Ð¸ÑÑÐ¾ÑÐ½Ð¸ÐºÐ¾Ð² ÑÐ°Ð´Ð¸Ð¾Ð¸Ð·Ð»ÑÑÐµÐ½Ð¸Ñ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð°Ð½ÑÐ°Ð¼Ð±Ð»Ñ ÑÐ°Ð´Ð¸Ð°Ð»ÑÐ½Ð¾-Ð±Ð°Ð·Ð¸ÑÐ½ÑÑ ÑÑÐ½ÐºÑÐ¸Ð¹
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Recognition of the type of radio source based on radial basis functions
Creators: name: ÐÐ²Ð°Ð½Ð½Ð¸ÐºÐ¾Ð²Ð°, ÐÐ¸ÐºÑÐ¾ÑÐ¸Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: Ð Ð°Ð´Ð¸Ð¾Ð»Ð¾ÐºÐ°ÑÐ¸Ð¾Ð½Ð½ÑÐµ ÑÐ¸ÑÑÐµÐ¼Ñ
ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ðµ
ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ
ÑÐ°Ð´Ð¸Ð°Ð»ÑÐ½Ð¾-Ð±Ð°Ð·Ð¸ÑÐ½ÑÐµ ÑÑÐ½ÐºÑÐ¸Ð¸
recognition
classification
radial basis functions

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description: The aim is recognition of the type of radio source under the condition of linear inseparability from individual radiations in the feature space. Methods used in the recognition task were considered. Often, they are based on a clear model of a decision on the type of source, do not consider the tuning of measured parameters, do not consider the priori uncertainty of radio monitoring data. The work proposed an algorithm based on the nonparametric Parzen method, which allows calculating probability estimates directly from the training set. Classifier is presented as a radial-basis functions neural network. To form hidden layer neurons, it is proposed to use an algorithm based on the rough set theory. With its application it is possible to set the number of clusters optimally, in contrast to k-means, as well as to attribute the point of feature space to several clusters. The result is a program model of classifier, which is embedded in the radio monitoring software.