Radar group target recognition based on HRRPs and weighted mean shift clustering
نویسندگان
چکیده
منابع مشابه
A Weighted Adaptive Mean Shift Clustering Algorithm
The mean shift algorithm is a nonparametric clustering technique that does not make assumptions on the number of clusters and on their shapes. It achieves this goal by performing kernel density estimation, and iteratively locating the local maxima of the kernel mixture. The set of points that converge to the same mode defines a cluster. While appealing, the performance of the mean shift algorit...
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Mean shift is a nonparametric clustering technique that does not require the number of clusters in input and can find clusters of arbitrary shapes. While appealing, the performance of the mean shift algorithm is sensitive to the selection of the bandwidth, and can fail to capture the correct clustering structure when multiple modes exist in one cluster. DBSCAN is an efficient density based clus...
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Cluster analysis is a useful tool for data analysis. Clustering methods are used to partition a data set into clusters such that the data points in the same cluster are the most similar to each other and the data points in the different clusters are the most dissimilar. The mean shift was originally used as a kernel-type weighted mean procedure that had been proposed as a clustering algorithm. ...
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The kernel bandwidth of the classical Mean-Shift tracking algorithm is fixed, and it usually results in tracking failure when the target’s size changes. A kernel bandwidth adaptive Mean-Shift tracking algorithm is presented with frame difference method to solve the question in this paper. According to the targets’ size obtained from the inter-frame difference method, the bandwidth matrix of ker...
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ژورنال
عنوان ژورنال: Journal of Systems Engineering and Electronics
سال: 2020
ISSN: 1004-4132
DOI: 10.23919/jsee.2020.000087