LMS-Based Algorithms

  • Paulo Sergio Ramirez Diniz
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 399)

Abstract

There are a number of algorithms for adaptive filters which are derived from the conventional LMS algorithm discussed in the previous chapter. The objective of the alternative LMS-based algorithms is either to reduce computational complexity or convergence time. In this chapter, four LMS-based algorithms are presented and analyzed, namely, the quantized-error algorithms [1]–[10], the frequency-domain (or transform-domain) LMS algorithm [11]–[13], the normalized LMS algorithm [14], and the LMS-Newton algorithm [15]–[16]. Several algorithms that are related to the main algorithms presented in this chapter are also briefly discussed.

Keywords

Attenuation Covariance Expense Autocorrelation Convolution 

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Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Paulo Sergio Ramirez Diniz
    • 1
  1. 1.Federal University of Rio de JaneiroBrazil

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