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The distributed estimation performance of multitask diffusion affine projection (AP) algorithm (MD-APA) will be greatly reduced under the impulsive noise interference. To overcome this defect, a robust MD-APA is derived by using M-estimate function (MD-APM) to resist the impulsive noise interference. The mean performance, mean square performance and steady-state performance of MD-APM algorithm are studied, and the convergence range of the step-size and the theoretical steady-state MSD are obtained. In addition, the computational complexity of MD-APM algorithm is analyzed in detail. Simulation experiments show that the proposed MD-APM algorithm has better estimation performance compared with MD-APA and MD-APSA under the impulsive noise interference, and its theoretical steady-state mean square deviation (MSD) can provide accurate prediction. [ABSTRACT FROM AUTHOR]

The generalized variable step-size diffusion continuous mixed p-norm (GVSS-DCMPN) algorithm is proposed in this paper, which is derived based on the improved continuous mixed p-norm (CMPN) strategy. In detail, a linear function is designed for the CMPN strategy. The proposed GVSS-DCMPN algorithm capable of exploiting various error norms to obtain performance improvement in non-Gaussian noise environment can be viewed as the generalization of the traditional p-norm-based algorithms in the sense of continuous errors. In particular, the GVSS-DCMPN algorithm transforms into the VSS-DCMPN algorithm when the slope of the linear function is set to 0. The computational complexity as well as the mean convergence is analyzed in the paper. Simulation results over the diffusion network show that the proposed algorithm achieves performance gain over some existing diffusion algorithms. [ABSTRACT FROM AUTHOR]

This paper proposes an improved variable regularization parameter (VRP) for sign subband adaptive filter, which is derived on the basis of the mean-square deviation (MSD) analysis. Since it is difficult to get access to the exact values of some quantities in the MSD, the VRP is calculated by minimizing the upper bound of a certain term which is employed to update the MSD. Moreover, a re-initialization mechanism that can enhance the tracking capability is developed. We also discuss the computational complexity of our finding. The proposed scheme enjoys more merits than several prior algorithms, which is illustrated by sufficient simulations designed for both the system identification and acoustic echo cancelation applications in the presence of impulsive noise. [ABSTRACT FROM AUTHOR]

Variable step size norm-constrained adaptive filtering algorithms are proposed in the paper. A variable step size is derived by minimizing the variance of the noise-free a posterior error. Thus, the update equation can obtain a reasonable step size at each iteration. Due to the introduction of variable step size, the proposed algorithms based on the constrained conditions of $$L_{1}$$ and $$L_{0}$$ norm have a significant advantage that the convergence rate is faster than some well-known algorithms in the sparse system. The simulation results illustrate the good performance of the proposed algorithms. [ABSTRACT FROM AUTHOR]