Convergence Rates of the POD–Greedy Method
Institute of Applied Analysis and Numerical Simulation, University of Stuttgart, Germany
Received: 4 July 2011
Revised: 18 April 2012
Iterative approximation algorithms are successfully applied in parametric approximation tasks. In particular, reduced basis methods make use of the so-called Greedy algorithm for approximating solution sets of parametrized partial differential equations. Recently, a priori convergence rate statements for this algorithm have been given (Buffa et al. 2009, Binev et al. 2010). The goal of the current study is the extension to time-dependent problems, which are typically approximated using the POD–Greedy algorithm (Haasdonk and Ohlberger 2008). In this algorithm, each greedy step is invoking a temporal compression step by performing a proper orthogonal decomposition (POD). Using a suitable coefficient representation of the POD–Greedy algorithm, we show that the existing convergence rate results of the Greedy algorithm can be extended. In particular, exponential or algebraic convergence rates of the Kolmogorov n-widths are maintained by the POD–Greedy algorithm.
Mathematics Subject Classification: 65D15 / 35B30 / 58B99 / 37C50
Key words: Greedy approximation / proper orthogonal decomposition / convergence rates / reduced Basis methods
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