Abstract
It can be shown that the update of the affine projection algorithm (APA) can be decomposed as the sum of two orthogonal vectors. One of these vectors is derived from an l 2 -norm optimization problem while the other one is simply a good initialization vector. By replacing the l 2 -norm optimization with the l k -norm optimization (with 0 < k ≤ 1), we can obtain a class of proportionate APAs (PAPAs). In this context, we evaluate the impact of the different l k -norm optimizations over the performance of the PAPAs.
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