Adaptive Filtering pp 139-193 | Cite as

# LMS-Based Algorithms

## 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, several LMS-based algorithms are presented and analyzed, namely, the quantized-error algorithms [1]–[11], the frequency–domain (or transform-domain) LMS algorithm [12]–[14], the normalized LMS algorithm [15], the LMS-Newton algorithm [16]–[17], and the affine projection algorithm [19]–[24]. Several algorithms that are related to the main algorithms presented in this chapter are also briefly discussed.

## Keywords

Input Signal Convergence Speed Adaptive Filter Convergence Factor Affine Projection Algorithm## Preview

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## References

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