Nonlinear Signal and Image Processing Theory Methods and Applications
Book Details :
LanguageEnglish
Pages557
FormatPDF
Size13.6 MB



Nonlinear Signal and Image Processing Theory Methods and Applications



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The Authors of Nonlinear Signal and Image Processing

Kenneth E. Barner and Gonzalo R. Arce are the editors of Nonlinear Signal and Image Processing Theory Methods and Applications PDF Book.

Main Contents of Nonlinear Signal and Image Processing PDF


  • Energy Conservation in Adaptive Filtering.
  • Fuzzy Methods in Nonlinear Signal Processing: Part I—Theory.
  • Fuzzy Methods in Nonlinear Signal Processing: Part II—Applications.
  • Time-Frequency Wigner Distribution Approach to Differential Equations.
  • Weighted Myriad Filters.
  • Data Traffic Modeling—A Signal Processing Perspective.
  • Nonlinear Adaptive Filters for Acoustic Echo Cancellation in Mobile Terminals.
  • Blind and Semiblind Channel Estimation.
  • Bayesian Image and Video Enhancement Using a Non-Gaussian Prior.
  • Statistical Image Modeling and Processing Using Wavelet-Domain Hidden Markov Models.
  • Self-Organizing Maps and Their Applications in Image Processing, Information Organization, and Retrieval.
  • Nonlinear Techniques for Color Image Processing.
  • Genetic Regulatory Networks: A Nonlinear Signal Processing Perspective.

Preface to Nonlinear Signal and Image Processing PDF


Nonlinear signal processing methods continue to grow in popularity and use. This growth is due to one factor—performance.


While it is true that linear methods continue to dominate in current practice, nonlinear methods are making steady progress in moving from theoretical explorations to practical implementations.

Nonlinear Signal and Image Processing PDF Free Download

Clearly, the advances in computing performance have accelerated this progress by making nonlinear methods more practical.

Additionally, nonlinear theory continues to grow and yield a firm foundation upon which nonlinear methods can be developed, optimized, and analyzed.

Nonlinear methods are thus being applied to address many of the most interesting and challenging signal processing problems of the day.

This Nonlinear Signal and Image Processing book details recent advances in nonlinear theory and methods. A wide array of contemporary applications in which nonlinear methods are being applied to address challenging open problems are also presented.

Although there is no single theory under which nonlinear methods are unified— these approaches are defined simply by what they are not, namely, linear— significant advances have been made in recent years in several branches of nonlinear theory.

The first set of chapters in the Nonlinear Signal and Image Processing book is therefore focused on recent advances in nonlinear signal processing theory.

This set of chapters targets three critical areas of theory:

(1) filter analysis,

(2) nonlinear filter class design, and

(3) signal analysis.

Nonlinear Signal and Image Processing PDF Free Download

The filter analysis presented utilizes new nonlinear approaches to analyzing the performance of adaptive filters. By utilizing nonlinear analysis, adaptive filters can be characterized in terms of a state-space model that lends greater insight.

Although no single theory unites the large number of nonlinear approaches reported in the literature, approaches founded on maximum likelihood principles define large filter classes that can address many challenging problems.

Here, we present two such filter classes: fuzzy ordering theory-based filters and myriad filters. Fuzzy ordering unites the theories of rank ordering and fuzzy relations to yield a broad class of robust filters.

Myriad filters are also a robust class of filters designed specifically, in this case, to address applications with stable distributions statistics.

The signal analysis presented here is based on time-frequency distributions. Although time-frequency distributions have been studied for some time, the current results presented here show that the Wigner distribution can be represented as a dynamic equation, the solution of which is an ordinary or partial differential equation.

The advantage of this approach is the insight into the nature of the solution provided by the analysis.

Although this first set of chapters is focused primarily on theory, each includes numerous examples and applications illustrating the advantages of nonlinear approaches.

Nonlinear Signal and Image Processing PDF Free Download

The remainder of the Nonlinear Signal and Image Processing book focuses on the application of nonlinear methods to a wide array of contemporary applications.

Nonlinear approaches, once used only in niche problems, are now becoming ubiquitous across the broad spectrum of applications that have signal processing components.

Of the numerous important applications now dominating researcher efforts, we have chosen to focus on applications in communications and networking, imaging and video, and genomics.

Within the area of communications and networking, methods and results are presented for data traffic modeling, echo cancellation in mobile terminals, and blind and semiblind channel estimation.

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Imaging and video, natural applications for nonlinear approaches due to the nonstationarity of the signals and the nonlinearity of the human visual system, are addressed in several chapters.

Specifically, current results on image and video enhancement, wavelet domain statistical image modeling and processing, image information organization and retrieval, and color image processing are presented.

While imaging applications have, for some time, been addressed through nonlinear approaches, an increasingly important, but less mature, application certain to benefit from nonlinear approaches is the growing field of genomics.

The application of nonlinear methods to select genomic applications is presented in a chapter on genetic regulatory networks.


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