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Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics
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Machine Intelligence and Signal Processing (Paperback, 1st ed. 2016)
Loot Price: R3,327
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Machine Intelligence and Signal Processing (Paperback, 1st ed. 2016)
Series: Advances in Intelligent Systems and Computing, 390
Expected to ship within 10 - 15 working days
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This book comprises chapters on key problems in machine learning
and signal processing arenas. The contents of the book are a result
of a 2014 Workshop on Machine Intelligence and Signal Processing
held at the Indraprastha Institute of Information Technology.
Traditionally, signal processing and machine learning were
considered to be separate areas of research. However in recent
times the two communities are getting closer. In a very abstract
fashion, signal processing is the study of operator design. The
contributions of signal processing had been to device operators for
restoration, compression, etc. Applied Mathematicians were more
interested in operator analysis. Nowadays signal processing
research is gravitating towards operator learning - instead of
designing operators based on heuristics (for example wavelets), the
trend is to learn these operators (for example dictionary
learning). And thus, the gap between signal processing and machine
learning is fast converging. The 2014 Workshop on Machine
Intelligence and Signal Processing was one of the few unique events
that are focused on the convergence of the two fields. The book is
comprised of chapters based on the top presentations at the
workshop. This book has three chapters on various topics of
biometrics - two are on face detection and one on iris recognition;
all from top researchers in their field. There are four chapters on
different biomedical signal / image processing problems. Two of
these are on retinal vessel classification and extraction; one on
biomedical signal acquisition and the fourth one on region
detection. There are three chapters on data analysis - a topic
gaining immense popularity in industry and academia. One of these
shows a novel use of compressed sensing in missing sales data
interpolation. Another chapter is on spam detection and the third
one is on simple one-shot movie rating prediction. Four other
chapters cover various cutting edge miscellaneous topics on
character recognition, software effort prediction, speech
recognition and non-linear sparse recovery. The contents of this
book will prove useful to researchers, professionals and students
in the domains of machine learning and signal processing.
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