Abstract
To improve the performance of identifying the block-sparse systems, firstly, a new sparsity aware block-sparse proportionate affine projection algorithm (BS-PAPA) with a fixed zero attractor is proposed in this paper. The proposed algorithm is obtained by integrating a weighted \(l_{0}\)-norm penalty into the cost function of the BS-PAPA. Adding the penalty results in zero attraction terms in the weight update recursive equation of the BS-PAPA, which helps in the shrinkage of inactive coefficients. The proposed algorithm is named \(l_{0}\)-block-sparse proportionate affine projection algorithm (\(l_{0}\)-BS-PAPA). The convergence analysis in the mean is derived for the \(l_{0}\)-BS-PAPA. Secondly, for applications having time varying measurement noise, an adaptive zero attractor \(l_{0}\)-BS-PAPA is also developed by adaptive optimisation of the zero attractor. This one is more robust to the varying degree of measurement noise than the former. A variable step-size \(l_{0}\)-BS-PAPA is also introduced to further enhance the performance of the \(l_{0}\)-BS-PAPA. Computer simulation experiments reveal that the \(l_{0}\)-BS-PAPA outperforms the existing algorithms in block-sparse systems in terms of convergence rate, normalised misalignment, and tracking ability.
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Boopalan, S.M., Alagala, S. A New Affine Projection Algorithm with Adaptive \(l_{0}\)-norm Constraint for Block-Sparse System Identification. Circuits Syst Signal Process 42, 1792–1807 (2023). https://doi.org/10.1007/s00034-022-02197-y
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DOI: https://doi.org/10.1007/s00034-022-02197-y