書誌事項

Theory and design of adaptive filters

John R. Treichler, C. Richard Johnson,Jr., Michael G. Larimore ; with an appendix by Texas Instruments and Teknekron Communications Systems

(Topics in digital signal processing)(A Wiley-Interscience publication)

Wiley, c1987

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注記

Bibliography: p. 331-338

内容説明・目次

内容説明

A comprehensive collection of adaptive filtering concepts, algorithm forms, behavioral insights, and application guidelines useful for the engineer interested in designing adaptive filters for various applications and for students needing a method pedagogy for initiation of basic research in adaptive theory. The analysis and design of three basic classes of adaptive filters are presented: adaptive-finite-impulse- response (FIR) filters; adaptive-infinite-impulse-response (IRR) filters; and Adaptive property restoring filters. For the widely used FIR filters, the book provides useful analytical tools and guidelines.For the more recently developed filters, it focuses on emerging theoretical foundations and suggested applications. The material is supplemented with listings of FORTRAN codes for basic algorithms and a real-time solution to one adaptive FIR filter problem using a Texas Instruments signal processing chip.

目次

  • THE NEED FOR ADAPTIVE FILTERING: Removal of Power Line Hum From Medical Instruments
  • Adaptive Differential Pulse Code Modulation
  • Equalization of Troposcatter Communication Signals
  • Generality and Commonality
  • BASIC PRINCIPLES OF ADAPTIVE FILTERING: The FIR Linear Combiner
  • Number Guessing Games
  • Single-Integer Guessing Games
  • Multiple- Integer Guessing Games
  • Multiple Real Numbers Guessing Games
  • Adaptive Filter Algorithm Interpretation
  • AN ANALYTICAL FRAMEWORK FOR DEVELOPNG ADAPTIVE ALGORITHMS: Background and Direction
  • The Least Squares Problem
  • Basic Formulation
  • Reduction to the Normal Equations
  • Direct Solution to the Optimal Vector
  • The Meaning of P and P Examples
  • Matching a Pure Delay
  • Matching a Rotated Phasor
  • Two Solution Technique
  • Direct Inversion
  • Iterative Approximation
  • Computational Comparisons
  • Consolidation
  • The Least Mean Square Problem
  • Formulation
  • A Brief Review of Stochastic Process
  • Ensemble Averages
  • An Example
  • Stationarity
  • The Concept of White Noise.

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