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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 Processing volume 2011, Article number: 484383 (2011)
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.
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Shams Esfand Abadi, M., Moradiani, F. Mean-Square Performance Analysis of the Family of Selective Partial Update NLMS and Affine Projection Adaptive Filter Algorithms in Nonstationary Environment. EURASIP J. Adv. Signal Process. 2011, 484383 (2011). https://doi.org/10.1155/2011/484383
- Information Technology
- Energy Conservation
- Quantum Information
- General Framework
- Tracking Performance