A Robust Set-membership Affine Projection Algorithm Based on Outlier Estimation Method

This paper describes an improved set-membership affine projection algorithm by combing the median absolute deviation (MAD) technique and set-membership affine projection (SMAP) algorithm. The quality of given data is usually closely related to the robustness of employed algorithm, in particular, the time series outliers can affect the convergence speed of employed approach. In this paper, the MAD method and SMAP algorithm are applied to eliminate the outliers of given time sequence and data selective adaptive filtering, respectively, and the convergence radius magnitude analysis and spatial structure of generalized algorithm update process of proposed approach are provided. Numerical simulation is given to illustrative the effectiveness of proposed approach.

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