Mean-Square Performance of a Family of Affine Projection Algorithms

Affine projection algorithms are useful adaptive filters whose main purpose is to speed the convergence of LMS-type filters. Most analytical results on affine projection algorithms assume special regression models or Gaussian regression data. The available analysis also treat different affine projection filters separately. This paper provides a unified treatment of the mean-square error, tracking, and transient performances of a family of affine projection algorithms. The treatment relies on energy conservation arguments and does not restrict the regressors to specific models or to a Gaussian distribution. Simulation results illustrate the analysis and the derived performance expressions.


Published in:
IEEE Transactions on Signal Processing, 52, 1, 90-102
Year:
2004
Publisher:
Institute of Electrical and Electronics Engineers
ISSN:
1053-587X
Laboratories:




 Record created 2017-12-19, last modified 2018-03-17


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