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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