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Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics
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Resolving Spectral Mixtures, Volume 30 - With Applications from Ultrafast Time-Resolved Spectroscopy to Super-Resolution Imaging (Hardcover)
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Resolving Spectral Mixtures, Volume 30 - With Applications from Ultrafast Time-Resolved Spectroscopy to Super-Resolution Imaging (Hardcover)
Series: Data Handling in Science and Technology
Expected to ship within 10 - 15 working days
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Resolving Spectral Mixtures: With Applications from Ultrafast
Time-Resolved Spectroscopy to Superresolution Imaging offers a
comprehensive look into the most important models and frameworks
essential to resolving the spectral unmixing problem-from
multivariate curve resolution and multi-way analysis to Bayesian
positive source separation and nonlinear unmixing. Unravelling
total spectral data into the contributions from individual unknown
components with limited prior information is a complex problem that
has attracted continuous interest for almost four decades. Spectral
unmixing is a topic of interest in statistics, chemometrics, signal
processing, and image analysis. For decades, researchers from these
fields were often unaware of the work in other disciplines due to
their different scientific and technical backgrounds and interest
in different objects or samples. This led to the development of
quite different approaches to solving the same problem. This
multi-authored book will bridge the gap between disciplines with
contributions from a number of well-known and strongly active
chemometric and signal processing research groups. Among chemists,
multivariate curve resolution methods are preferred to extract
information about the nature, amount, and location in time
(process) and space (imaging and microscopy) of chemical
constituents in complex samples. In signal processing, assumptions
are usually around statistical independence of the extracted
components. However, the chapters include the complexity of the
spectral data to be unmixed as well as dimensionality and size of
the data sets. Advanced spectroscopy is the key thread linking the
different chapters. Applications cover a large part of the
electromagnetic spectrum. Time-resolution ranges from femtosecond
to second in process spectroscopy and spatial resolution covers the
submicronic to macroscopic scale in hyperspectral imaging.
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