Mean-square performance analysis of the family of selective partial update NLMS and affine projection adaptive filter algorithms in nonstationary environment

Authors:
Mohammad Shams Esfand Abadi;Fatemeh Moradiani
Affiliations:
Faculty of Electrical and Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran;Faculty of Electrical and Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran
Venue:
EURASIP Journal on Advances in Signal Processing - Special issue on recent advances in theory and methods for nonstationary signal analysis
Year:
2011

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Abstract

We present the general framework formean-square performance analysis of the selective partial update affine projection algorithm (SPU-APA) and the family of SPU normalized least mean-squares (SPU-NLMS) adaptive filter algorithms in nonstationary environment. Based on this the tracking performance of Max-NLMS, N-Max NLMS and the various types of SPU-NLMS and SPU-APA can be analyzed in a unified way. The 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 derived expressions are useful in predicting the performances of this family of adaptive filters in nonstationary environment.