Fundamentals of Nonlinear Digital Filtering
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Summary
Fundamentals of Nonlinear Digital Filtering is the first book of its kind, presenting and evaluating current methods and applications in nonlinear digital filtering. Written for professors, researchers, and application engineers, as well as for serious students of signal processing, this is the only book available that functions as both a reference handbook and a textbook. Solid introductory material, balanced coverage of theoretical and practical aspects, and dozens of examples provide you with a self-contained, comprehensive information source on nonlinear filtering and its applications.
Table of Contents
Nonlinear Signal Processing
Signal Processing Model
Signal and Noise Models
Fundamental Problems in Noise Removal
Algorithms
Statistical Preliminaries
Random Variables and Distributions
Signal and Noise Models
Estimation
Some Useful Distributions
1001 Solutions
Trimmed Mean Filters
Other Trimmed Mean Filters
L-Filters
C-Filters (Ll-Filters)
Weighted Median Filters
Ranked-Order and Weighted Order Statistic Filters
Multistage Median Filters
Median Hybrid Filters
Edge-Enhancing Selective Filters
Rank Selection Filters
M-Filters
R-Filters
Weighted Majority with Minimum Range Filters
Nonlinear Mean Filters
Stack Filters
Generalizations of Stack Filters
Morphological Filters
Soft Morphological Filters
Polynomial Filters
Data-Dependent Filters
Decision-Based Filters
Iterative, Cascaded, and Recursive Filters
Some Numerical Measures of Nonlinear Filters
Discussion
Statistical Analysis and Optimization of Nonlinear Filters
Methods Based on Order Statistics
Stack Filters
Multistage and Hybrid Filters
Discussion
Exercises
Bibliography
Index
