An increasing complexity of models used to predict real-world
systems leads to the need for algorithms to replace complex models
with far simpler ones, while preserving the accuracy of the
predictions. This two-volume handbook covers methods as well as
applications. This first volume focuses on real-time control
theory, data assimilation, real-time visualization,
high-dimensional state spaces and interaction of different
reduction techniques.
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