Description
Book SynopsisNonlinear signal and image processing methods are fast emerging as an alternative to established linear methods for meeting the challenges of increasingly sophisticated applications. Advances in computing performance and nonlinear theory are making nonlinear techniques not only viable, but practical.
This book details recent advances in nonlinear theory and methods and explores an array of modern signal and image processing applications. The first several chapters focus on nonlinear signal processing theory, targeting three critical areas: filter analysis, nonlinear filter class design, and signal analysis. The remaining chapters explore nonlinear approaches across the broad spectrum of applications with signal processing components, from data traffic modeling and image enhancement to cutting edge applications in genomics.
All of the chapters were contributed by well-known theorists and application-driven researchers who explore current and emerging nonlinear methods
Table of Contents
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 Semi-Blind 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.
