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  • Research Article
  • Open Access

Mean-Square Performance Analysis of the Family of Selective Partial Update NLMS and Affine Projection Adaptive Filter Algorithms in Nonstationary Environment

EURASIP Journal on Advances in Signal Processing20102011:484383

  • Received: 30 June 2010
  • Accepted: 11 October 2010
  • Published:


We present the general framework for mean-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.


  • Information Technology
  • Energy Conservation
  • Quantum Information
  • General Framework
  • Tracking Performance

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Authors’ Affiliations

Faculty of Electrical and Computer Engineering, Shahid Rajaee Teacher Training University, P.O. Box 16785-163, Tehran, Iran