Kernel-Based Subspace Learning on Riemannian Manifolds for Visual Recognition
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DOI: 10.1007/s11063-019-10083-z
Abstract: Covariance matrices have attracted increasing attention for data representation in many computer vision tasks. The nonsingular covariance matrices are regarded as points on Riemannian manifolds rather than Euclidean space. A common technique for classification on… read more here.
Keywords: rkhs; space; kernel based; euclidean space ... See more keywords
Extended H∞ Filtering in RKHS for Nonlinear Systems With Uncertainty
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Circuits and Systems II: Express Briefs"
DOI: 10.1109/tcsii.2024.3522913
Abstract: Uncertainties in nonlinear systems can significantly hinder the effectiveness of traditional filtering methods, leading to suboptimal state estimation and compromising overall performance and robustness. Therefore, an extended H $_{\infty }$ filtering based on reproducing kernel… read more here.
Keywords: rkhs; tex math; nonlinear systems; inline formula ... See more keywords