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ISS in Spatial Lp Norms for Hyperbolic PDEs
2018The chapter deals with the derivation of ISS estimates expressed in spatial \( L^{p} \) norms for 1-D, first-order, hyperbolic PDEs with a constant transport velocity. Two different methodologies for deriving ISS estimates are provided. The first methodology is the use of ISS-Lyapunov Functionals (ISS-LFs).
Iasson Karafyllis, Miroslav Krstic
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ISS in Spatial Lp Norms for Parabolic PDEs
2018The chapter provides ISS estimates of the solutions of 1-D, parabolic PDEs with respect to boundary and distributed disturbances, which are expressed in weighted spatial \( L^{p} \) norms of the state with \( 1 \le p \le + \infty \). A novel methodology for the derivation of the ISS estimates is presented: the use of an ISS-Lyapunov Functional Under ...
Iasson Karafyllis, Miroslav Krstic
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Tensor Robust Principal Component Analysis with a New Tensor Nuclear Norm
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020Canyi Lu, Jiashi Feng, Yudong Chen
exaly
Principal Component Analysis Based on L1-Norm Maximization
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008N Kwak
exaly
Fast and Accurate Matrix Completion via Truncated Nuclear Norm Regularization
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013Yao Hu, Debing Zhang, Xuelong Li
exaly

