Adaptive mixed-norm filtering algorithm based on S αSG noise model

Authors:
Daifeng Zha;Tianshuang Qiu
Affiliations:
School of Electronic and Information Engineering, Dalian University of Technology, Dalian 116024, People's Republic of China;School of Electronic and Information Engineering, Dalian University of Technology, Dalian 116024, People's Republic of China
Venue:
Digital Signal Processing
Year:
2007

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Abstract

The standard mixed-norm filtering algorithm exhibits slow convergence in stable distribution environment, requires a stationary operating environment, and employs a constant step-size that needs to be determined a priori. We proposed a new adaptive mixed moments filtering algorithm based on S@aSG (symmetry @a-stable Gaussian) noise model. The simulation experiments show that the proposed algorithm exhibits increased convergence rate and stability performance than the conventional mixed-norm algorithm.