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Books > Reference & Interdisciplinary > Communication studies > Information theory > Cybernetics & systems theory
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Linear Prediction Theory - A Mathematical Basis for Adaptive Systems (Paperback, Softcover reprint of the original 1st ed. 1990)
Loot Price: R1,446
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Linear Prediction Theory - A Mathematical Basis for Adaptive Systems (Paperback, Softcover reprint of the original 1st ed. 1990)
Series: Springer Series in Information Sciences, 21
Expected to ship within 18 - 22 working days
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Lnear prediction theory and the related algorithms have matured to
the point where they now form an integral part of many real-world
adaptive systems. When it is necessary to extract information from
a random process, we are frequently faced with the problem of
analyzing and solving special systems of linear equations. In the
general case these systems are overdetermined and may be
characterized by additional properties, such as update and
shift-invariance properties. Usually, one employs exact or
approximate least-squares methods to solve the resulting class of
linear equations. Mainly during the last decade, researchers in
various fields have contributed techniques and nomenclature for
this type of least-squares problem. This body of methods now
constitutes what we call the theory of linear prediction. The
immense interest that it has aroused clearly emerges from recent
advances in processor technology, which provide the means to
implement linear prediction algorithms, and to operate them in real
time. The practical effect is the occurrence of a new class of
high-performance adaptive systems for control, communications and
system identification applications. This monograph presumes a
background in discrete-time digital signal processing, including
Z-transforms, and a basic knowledge of discrete-time random
processes. One of the difficulties I have en countered while
writing this book is that many engineers and computer scientists
lack knowledge of fundamental mathematics and geometry."
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