| Summary: | A novel adaptive filtering (AF) algorithm is proposed for group-sparse system identifications. In the devised algorithm, a novel mixed error criterion (MEC) with two-order logarithm error, <i>p</i>-order errors and group sparse constraint method is devised to give a resistant to the impulsive noise. The proposed group-sparse MEC can fully use the known group-sparse characteristics in the cluster sparse systems, and it is derived and analyzed in detail. Various simulations are presented and analyzed to give a verification on the effectiveness of the developed group-sparse MEC algorithms, and the simulated results shown that the developed algorithm outperforms the previously developed sparse AF algorithms for identifying the systems.
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