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Adaptive Signal Models - Theory, Algorithms, and Audio Applications (Paperback, Softcover reprint of the original 1st ed. 1998)
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Adaptive Signal Models - Theory, Algorithms, and Audio Applications (Paperback, Softcover reprint of the original 1st ed. 1998)
Series: The Springer International Series in Engineering and Computer Science, 467
Expected to ship within 10 - 15 working days
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Adaptive Signal Models: Theory, Algorithms and Audio Applications
presents methods for deriving mathematical models of natural
signals. The introduction covers the fundamentals of
analysis-synthesis systems and signal representations. Some of the
topics in the introduction include perfect and near-perfect
reconstruction, the distinction between parametric and
nonparametric methods, the role of compaction in signal modeling,
basic and overcomplete signal expansions, and time-frequency
resolution issues. These topics arise throughout the book as do a
number of other topics such as filter banks and multiresolution.
The second chapter gives a detailed development of the sinusoidal
model as a parametric extension of the short-time Fourier
transform. This leads to multiresolution sinusoidal modeling
techniques in Chapter Three, where wavelet-like approaches are
merged with the sinusoidal model to yield improved models. In
Chapter Four, the analysis-synthesis residual is considered; for
realistic synthesis, the residual must be separately modeled after
coherent components (such as sinusoids) are removed. The residual
modeling approach is based on psychoacoustically motivated
nonuniform filter banks. Chapter Five deals with pitch-synchronous
versions of both the wavelet and the Fourier transform; these allow
for compact models of pseudo-periodic signals. Chapter Six
discusses recent algorithms for deriving signal representations
based on time-frequency atoms; primarily, the matching pursuit
algorithm is reviewed and extended. The signal models discussed in
the book are compact, adaptive, parametric, time-frequency
representations that are useful for analysis, coding, modification,
and synthesis of natural signals such as audio. The models are all
interpreted as methods for decomposing a signal in terms of
fundamental time-frequency atoms; these interpretations, as well as
the adaptive and parametric natures of the models, serve to link
the various methods dealt with in the text. Adaptive Signal Models:
Theory, Algorithms and Audio Applications serves as an excellent
reference for researchers of signal processing and may be used as a
text for advanced courses on the topic.
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