Mean-square performance analysis of the family of selective partial update and selective regressor affine projection algorithms

• Published in: Signal processing Vol. 90; no. 1; pp. 197 - 206
• Main Authors: Abadi, Mohammad Shams Esfand, Palangi, Hamid
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 2010; Elsevier
• Subjects: Adaptive filter; Adaptive filters; Affine projection; Algorithms; Applied sciences; Detection, estimation, filtering, equalization, prediction; Energy conservation; Exact sciences and technology; Forecasting; Formalism; Gaussian; Information, signal and communications theory; Mean-square performance; Miscellaneous; Projection; Regression analysis; Selective partial update; Selective regressor; Signal and communications theory; Signal processing; Signal, noise; Strontium; Subband; Telecommunications and information theory; Affine projection; Selective regressor; Energy conservation; Selective partial update; Subband; Adaptive filter; Mean-square performance; Performance evaluation; Subband decomposition; Adaptive algorithm; Gaussian distribution; Updating; Affine transformation; Simulation; Signal processing
• ISSN: 0165-1684; 1872-7557
• DOI: 10.1016/j.sigpro.2009.06.013

In this paper we present a general formalism for the establishment and mean-square performance analysis of the family of selective partial update affine projection (SPU-AP), selective regressor affine projection (SR-AP), and selective partial update subband adaptive filter (SPU-SAF) algorithms. This analysis is based on energy conservation arguments and does not need to assume a Gaussian or white distribution for the regressors. We demonstrate through simulations that the results are useful in predicting the performance of these adaptive filter algorithms.