Model Reduction of Parametrized Systems

The special volume offers a global guide to new concepts and approaches concerning the following topics: reduced basis methods, proper orthogonal decomposition, proper generalized decomposition, approximation theory related to model reduction, learning theory and compressed sensing, stochastic and high-dimensional problems, system-theoretic methods, nonlinear model reduction, reduction of coupled problems/multiphysics, optimization and optimal control, state estimation and control, reduced order models and domain decomposition methods, Krylov-subspace and interpolatory methods, and applications to real industrial and complex problems.

The book represents the state of the art in the development of reduced order methods. It contains contributions from internationally respected experts, guaranteeing a wide range of expertise and topics. Further, it reflects an important effor

t, carried out over the last 12 years, to build a growing research community in this field.


Though not a textbook, some of the chapters can be used as reference materials or lecture notes for classes and tutorials (doctoral schools, master classes).

Volumul special ofera un ghid global pentru noi concepte si abordari referitoare la urmatoarele subiecte: metode de baza reduse, descompunere ortogonala adecvata, descompunere generalizata adecvata, teoria aproximarii legata de reducerea modelelor, teoria invatarii si detectarea comprimata, probleme stocastice si de inalta dimensiune, sistem -metode teoretice, reducerea modelului neliniar, reducerea problemelor cuplate / multifizica, optimizare si control optim, estimarea si controlul starii, modele de ordine redusa si metode de descompunere a domeniului, metode interpolatorii si subspatiului Krylov si aplicatii la probleme industriale si complexe reale. cartea reprezinta stadiul tehnicii in dezvoltarea metodelor de comanda redusa.