Nonlinear Digital Filters: Analysis and Applications

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Academic Press, Jul 27, 2010 - Technology & Engineering - 216 pages
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Nonlinear Digital Filters provides an easy to understand overview of nonlinear behavior in digital filters, showing how it can be utilized or avoided when operating nonlinear digital filters.

It gives techniques for analyzing discrete-time systems with discontinuous linearity, enabling the analysis of other nonlinear discrete-time systems, such as sigma delta modulators, digital phase lock loops, and turbo coders. It uses new methods based on symbolic dynamics, enabling the engineer to easily operate reliable nonlinear digital filters.

It gives practical, 'real-world' applications of nonlinear digital filters and contains many examples.

The book is ideal for professional engineers working with signal processing applications, as well as advanced undergraduates and graduates conducting a nonlinear filter analysis project.

  • Uses new methods based on symbolic dynamics, enabling the engineer more easily to operate reliable nonlinear digital filters
  • Gives practical, "real-world" applications of nonlinear digital filter
  • Includes many examples.

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Chapter 1 Introduction
Chapter 2 Reviews
Chapter 3 Quantization in Digital Filters
Chapter 4 Saturation in Digital Filters
Chapter 5 Autonomous Response of Digital Filters with Twos Complement Arithmetic
Chapter 6 Step Response of Digital Filters with Twos Complement Arithmetic
Chapter 7 Sinusoidal Response of Digital Filters with Twos Complement Arithmetic
Chapter 8 Twos Complement Arithmetic in Complex Digital Filters
Chapter 9 Quantization and Twos Complement Arithmetic in Digital Filters
Chapter 10 Properties and Applications of Digital Filters with Nonlinearities
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Page 17 - Rn, then it is said to be asymptotically stable in the large or globally asymptotically stable.
Page 6 - A fractal is a geometric pattern that is repeated at ever smaller scales to produce irregular shapes and surfaces that cannot be represented by classical geometry. Fractals are used especially in computer modeling of irregular patterns and structures in nature.
Page 12 - A is a fuzzy set defined in the physical domain of x). A compound fuzzy proposition is a composition of atomic fuzzy propositions using the connectives "and," "or," and "not" which represent fuzzy intersection, fuzzy union, and fuzzy complement, respectively.
Page 12 - Roughly speaking, if a variable can take words in natural languages as its values, it is called a linguistic variable. Now the question is how to formulate the words in mathematical terms?
Page 12 - U is the actual physical domain in which the linguistic variable X takes its quantitative (crisp) values; in Example 5.1, U = [0, Vmax]. • M is a semantic rule that relates each linguistic value in T with a fuzzy set in U; in Example 5.1, M relates "slow," "medium," and "fast" with the membership functions shown in Fig.
Page 13 - We need a theory to formulate human knowledge in a systematic manner and put it into engineering systems, together with other information like mathematical models and sensory measurements.

About the author (2010)

Dr. Ling received the B.Eng.(Hons) and M.Phil. degrees from the department of Electrical and Electronic Engineering, the Hong Kong University of Science and Technology, in 1997 and 2000, respectively, and a Ph.D. degree in the department of Electronic and Information Engineering from the Hong Kong Polytechnic University in 2003. In 2004, he joined the King's College London as a Lecturer. His research interests include discontinuous nonlinear system theory with applications to digital filters with two's complement arithmetic and sigma delta modulators, continuous constrained optimization theory with applications to filters, filter banks and sigma delta modulators design, filter banks and wavelets theory with applications to multimedia and biomedical signal processing, and fuzzy, impulsive and optimal control theory with applications to sigma delta modulators and power electronics.

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