A simple and flexible model order reduction method for FFT-based homogenization problems using a sparse sampling technique

This work is concerned with the development of a novel model order reduction technique for FFT solvers. The underlying concept is a compressed sensing technique which allows the reconstruction of highly incomplete data using non-linear recovery algorithms based on convex optimization, provided the d...

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