Introduction

Chapter
Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Abstract

The area of adaptive filtering is a very importantone in the vast field of Signal Processing. Adaptive filters areubiquitous in current technology. System identificaction, equalization for communication systems, active noise cancellation,speech processing, sonar, seismology, beamforming, etc, are a few examples from a large set of applications were adaptive filters are used to solve different kinds of problems. In this chapter we provide a short introduction to the adaptive filtering problem and to the different aspects that should be taken into account when choosing or designing an adaptive filter for a particular application.

Keywords

Adaptive Filter Weight Little Square Recursive Little Square Steady State Error Wiener Filter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    S. Haykin, Adaptive Filter Theory, 4th edn. (Prentice-Hall, Upper Saddle River, 2002)Google Scholar
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    D.G. Manolakis, V.K. Ingle, S.M. Kogon, Statistical and Adaptive Signal Processing (Artech House, Norwood, 2005)Google Scholar
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    P.S.R. Diniz, Adaptive Filtering: Algorithms And Practical Implementation, 3rd edn. (Springer, Boston, 2008)MATHGoogle Scholar
  4. 4.
    S. Haykin, Signal processing: where physics and mathematics meet. IEEE Signal Process. Mag. 18, 6–7 (2001)CrossRefGoogle Scholar

Copyright information

© The Author(s) 2013

Authors and Affiliations

  1. 1.School of EngineeringUniversity of Buenos AiresBuenos AiresArgentina
  2. 2.Department of EngineeringUniversity of LeicesterLeicesterUK

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