Mathematical models are used to simulate, and sometimes control,
the behavior of physical and artificial processes such as the
weather and very large-scale integration (VLSI) circuits. The
increasing need for accuracy has led to the development of highly
complex models. However, in the presence of limited computational
accuracy and storage capabilities model reduction (system
approximation) is often necessary. Approximation of Large-Scale
Dynamical Systems provides a comprehensive picture of model
reduction, combining system theory with numerical linear algebra
and computational considerations. It addresses the issue of model
reduction and the resulting trade-offs between accuracy and
complexity. Special attention is given to numerical aspects,
simulation questions, and practical applications.
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