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Sparse system identification problems often exist in many applications, such as echo interference cancellation, sparse channel estimation, and adaptive beamforming. One of popular adaptive sparse system identification (ASSI) methods is adopting only one sparse least mean square (LMS) filter. However, the adoption of only one sparse LMS filter cannot simultaneously achieve fast convergence speed and small steady-state mean state deviation (MSD). Unlike the conventional method, we propose andoi:10.1109/vtcspring.2014.7023132 dblp:conf/vtc/GuiKMA14 fatcat:qdh5kzlx6zdntid7jyrhutco3y