An affine projection algorithm using the inner product of input vectors

This paper proposes an affine projection algorithm (APA) using the inner product between input vectors. The existing APAs have fast convergence rate but large steady-state estimation errors. In order to reduce the estimation errors, the proposed algorithm adjusts the number of the input vectors by grouping of the input vectors. The grouping process uses the angle between a current input vector and past input vectors. The proposed algorithm puts the input vectors with a similar angle size into the same group and replaces input vectors in the group with the representative input vector. The angle interval for the grouping adjusts the number of groups and is gradually increasing to reduce the number of input vector at the steady state. This leads to reduce the steady-state estimation errors. The experimental results show that the proposed algorithm has small steady-state estimation errors comparing to the existing algorithms.