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Minimum error entropy with affine projection algorithm for robust adaptive filtering
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DOI：10.1016/j.dsp.2025.105198.png)
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Abstract
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Considering the similarity and correlation between the method of affine projection (AP) and minimum error entropy (MEE), we find that AP and MEE can be combined well, so a new robust adaptive filtering algorithm named APMEE was proposed. By optimizing the non-parametric estimator of quadratic Renyi's entropy of two individual errors in an observation interval with a l(2)-norm constraint on the weight vector, APMEE greatly improves the convergence speed and steady-state accuracy of adaptive filtering. Numerical simulation experiments of system identification and echo cancellation indicate that APMEE outperforms other algorithms based on affine projection.
Keywords:
Adaptive filter
Minimum error entropy
Affine projection
System identification
Echo cancellation
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PROCEEDINGS OF THE IEEE
PROCEEDINGS OF THE IEEEIF25.9
PREAI
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