Signal processing with alpha-stable distributions and applications
Signal processing with alpha-stable distributions and applications
Adaptive filtering approaches for non-Gaussian stable processes
ICASSP '95 Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02
Direction finding in non-Gaussian impulsive noise environments
Digital Signal Processing
Adaptive mixed-norm filtering algorithm based on S αSG noise model
Digital Signal Processing
Underwater sources location in non-Gaussian impulsive noise environments
Digital Signal Processing
Symmetric alpha-stable filter theory
IEEE Transactions on Signal Processing
A novel adaptive lattice filtering algorithm for alpha-stable processes
Digital Signal Processing
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The least mean p-norm (LMP) algorithm is an effective algorithm for processing the signal of @a-stable distribution. This paper proposes data block adaptive filtering algorithms for the @a-stable random processes based on the fractional lower order statistics (FLOS). The data block algorithms change the direction of coefficient increment vector by introducing a matrix which includes the information of more past input signal vectors than which are used in the LMP algorithm during the iteration process, taking full advantage of the past values of the gradient vector during the adaptation. Simulations studies indicate that the proposed algorithms increase convergence rate in non-Gaussian stable distribution noise environments compared to the existing algorithms based on FLOS summarized in this paper.