This paper proposes an \(L_{0}\) norm constraint memory improved proportionate affine projection algorithm with a lower computational complexity than the conventional \(L_{0}\) norm constraint improved proportionate affine projection algorithm. Particularly, to achieve a low computational complexity, we propose to remove the matrix before the zero attraction term. Moreover, the product of the proportionate matrix and input matrix is implemented using an efficient recursive scheme. Simulation results in acoustic echo cancellation context show that our algorithm not only significantly reduces the computational complexity but also achieves slightly improved steady-state misalignment.
['Zhaoxia Qu', 'Zongsheng Zheng']
An Efficient \(L_{0}\) Norm Constraint Memory Improved Proportionate Affine Projection Algorithm