Research output: Contribution to journal › Article › peer-review
We consider the possibilities of using stochastic approximation algorithms with randomization on the input under unknown but bounded interference in studying the clustering of data generated by a mixture of Gaussian distributions. The proposed algorithm, which is robust to external disturbances, allows us to process the data "on the fly" and has a high convergence rate. The operation of the algorithm is illustrated by examples of its use for clustering in various difficult conditions.
Original language | English |
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Pages (from-to) | 1403-1418 |
Number of pages | 16 |
Journal | Automation and Remote Control |
Volume | 80 |
Issue number | 8 |
DOIs | |
State | Published - 1 Aug 2019 |
ID: 46020243