Mean-square performance of a family of affine projection algorithms

By Hyun-Chool Shin, Ali H. Sayed. IEEE Transactions on Signal Processing, 2004

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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.

Subfields: Computational Mechanics, Signal Processing

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