Mean-Square Performance of Selective Partial Update Subband Adaptive Filters

Abstract

In this paper, we present a general formalism for the mean-square performance analysis of 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 this family of adaptive filters.

Keywords:

• Energy conservation
• Mean-square performance
• Selective partial update subband adaptive filter

Additional information

Notes on contributors

Mohammad Shams Esfand Abadi

Mohammad Shams Esfand Abadi graduated in Electrical Engineering from Mazandaran University, Mazandaran, Iran and the M. Sc. Degree in Electrical Engineering from Tarbiat Modares University, Tehran, Iran in 2000 and 2002, respectively and the PhD degree in Biomedical Engineering from Tarbiat Modares University, Tehran, Iran in 2007. Since 2004 he has been with the Department of Electrical Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran. During the fall of 2003, spring of the 2005, and again in the spring of 2007, he was a visiting scholar with the Signal Processing Group at the University of Stavanger, Norway. His research interests include digital filter theory and adaptive signal processing algorithms. E-mail: [email protected]