An LP empirical quadrature procedure for parametrized functions
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Publication:1681553
DOI10.1016/j.crma.2017.10.020zbMath1377.65074OpenAlexW2767249151MaRDI QIDQ1681553
Anthony T. Patera, Masayuki Yano
Publication date: 23 November 2017
Published in: Comptes Rendus. Mathématique. Académie des Sciences, Paris (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.crma.2017.10.020
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Cites Work
- A mathematical introduction to compressive sensing
- A necessary and sufficient condition for exact sparse recovery by \(\ell_1\) minimization
- Extensions of Gauss quadrature via linear programming
- Reduced basis approximation and a posteriori error estimation for affinely parametrized elliptic coercive partial differential equations. Application to transport and continuum mechanics.
- An `empirical interpolation' method: Application to efficient reduced-basis discretization of partial differential equations
- Structure-preserving, stability, and accuracy properties of the energy-conserving sampling and weighting method for the hyper reduction of nonlinear finite element dynamic models
- Sparse and Redundant Representations
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