In this paper, an M-estimate affine projection algorithm based on correntropy induced metric (MAPA-CIM) is proposed for robust sparse adaptive filtering. The proposed MAPA-CIM algorithm uses an M-estimate robust cost function with correntropy induced metric, which is derived by using the unconstrained minimization method. Simulation results show that the proposed MAPA-CIM algorithm has better convergence speed and lower steady-state misalignment for sparse system identification and echo cancellation scenarios in non-Gaussian environments with colored input signal over the usual adaptive filtering algorithms.
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