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Computational Methods for Approximation of Large-Scale Dynamical Systems (Hardcover)
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Computational Methods for Approximation of Large-Scale Dynamical Systems (Hardcover)
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These days, computer-based simulation is considered the
quintessential approach to exploring new ideas in the different
disciplines of science, engineering and technology (SET). To
perform simulations, a physical system needs to be modeled using
mathematics; these models are often represented by linear
time-invariant (LTI) continuous-time (CT) systems. Oftentimes these
systems are subject to additional algebraic constraints, leading to
first- or second-order differential-algebraic equations (DAEs),
otherwise known as descriptor systems. Such large-scale systems
generally lead to massive memory requirements and enormous
computational complexity, thus restricting frequent simulations,
which are required by many applications. To resolve these
complexities, the higher-dimensional system may be approximated by
a substantially lower-dimensional one through model order reduction
(MOR) techniques. Computational Methods for Approximation of
Large-Scale Dynamical Systems discusses computational techniques
for the MOR of large-scale sparse LTI CT systems. Although the book
puts emphasis on the MOR of descriptor systems, it begins by
showing and comparing the various MOR techniques for standard
systems. The book also discusses the low-rank alternating direction
implicit (LR-ADI) iteration and the issues related to solving the
Lyapunov equation of large-scale sparse LTI systems to compute the
low-rank Gramian factors, which are important components for
implementing the Gramian-based MOR. Although this book is primarly
aimed at post-graduate students and researchers of the various SET
disciplines, the basic contents of this book can be supplemental to
the advanced bachelor's-level students as well. It can also serve
as an invaluable reference to researchers working in academics and
industries alike. Features: Provides an up-to-date, step-by-step
guide for its readers. Each chapter develops theories and provides
necessary algorithms, worked examples, numerical experiments and
related exercises. With the combination of this book and its
supplementary materials, the reader gains a sound understanding of
the topic. The MATLAB (R) codes for some selected algorithms are
provided in the book. The solutions to the exercise problems,
experiment data sets and a digital copy of the software are
provided on the book's website; The numerical experiments use
real-world data sets obtained from industries and research
institutes.
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