Affine Projection Adaptive Filter with Variable Regularization

We propose two affine projection algorithms (APA)
with variable regularization parameter. The proposed algorithms
dynamically update the regularization parameter that is fixed in the
conventional regularized APA (R-APA) using a gradient descent
based approach. By introducing the normalized gradient, the proposed
algorithms give birth to an efficient and a robust update scheme for
the regularization parameter. Through experiments we demonstrate
that the proposed algorithms outperform conventional R-APA in
terms of the convergence rate and the misadjustment error.

Authors:

• Young-Seok Choi

Keywords:

• Affine projection
• regularization
• gradient descent
• system identification.

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