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Books > Science & Mathematics > Mathematics > Combinatorics & graph theory
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An Introduction to Compressed Sensing (Paperback)
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An Introduction to Compressed Sensing (Paperback)
Series: Computational Science and Engineering 22
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Compressed sensing is a relatively recent area of research that
refers to the recovery of high-dimensional but low-complexity
objects from a limited number of measurements. The topic has
applications to signal/image processing and computer algorithms,
and it draws from a variety of mathematical techniques such as
graph theory, probability theory, linear algebra, and optimization.
The author presents significant concepts never before discussed as
well as new advances in the theory, providing an in-depth
initiation to the field of compressed sensing. An Introduction to
Compressed Sensing contains substantial material on graph theory
and the design of binary measurement matrices, which is missing in
recent texts despite being poised to play a key role in the future
of compressed sensing theory. It also covers several new
developments in the field and is the only book to thoroughly study
the problem of matrix recovery. The book supplies relevant results
alongside their proofs in a compact and streamlined presentation
that is easy to navigate. The core audience for this book is
engineers, computer scientists, and statisticians who are
interested in compressed sensing. Professionals working in image
processing, speech processing, or seismic signal processing will
also find the book of interest.
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