Adaptive mixed-norm filtering algorithm based on SαSG noise model

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 SαSG (symmetry α-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.