Binary Polynomial Transforms And Non Linear Digital Filters
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Binary Polynomial Transforms and Non-Linear Digital Filters
This work offers a unified presentation of the theory of binary polynomial transforms and details their numerous applications in nonlinear signal processing. The book also: introduces the Rademacher logical functions; considers fast algorithms for computing Rademacher and polynomial logical functions; focuses attention on general auto- and cross-correlation functions; and more.;The work is intended for applied mathematicians; electrical, electronics and other engineers; computer scientists; and upper-level undergraduate and graduate students in these disciplines.
Nonlinear Filters for Image Processing
This text covers key mathematical principles and algorithms for nonlinear filters used in image processing. Readers will gain an in-depth understanding of the underlying mathematical and filter design methodologies needed to construct and use nonlinear filters in a variety of applications. The 11 chapters explore topics of contemporary interest as well as fundamentals drawn from nonlinear filtering's historical roots in mathematical morphology and digital signal processing. This book examines various filter options and the types of applications for which they are best suited. The presentation is rigorous, yet accessible to engineers with a solid background in mathematics.
Fundamentals of Nonlinear Digital Filtering
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.