Complex-valued proportionate affine projection Versoria algorithms and their combined-step-size variants for sparse system identification under impulsive noises

Huang, Fuyi; Zhang, Jiashu; Zhang, Sheng

doi:10.1016/j.dsp.2021.103209

Cited by 7 publications

(1 citation statement)

References 48 publications

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“…Complex-valued adaptive filtering algorithm has a wide range of engineering applications in radio systems [ 1 ], system identification [ 2 ], environment signal processing [ 3 ], and other fields. Generally speaking, complex-valued adaptive filtering algorithm is an extension of the real-valued adaptive filtering algorithm.…”

Section: Introductionmentioning

confidence: 99%

Generalized Maximum Complex Correntropy Augmented Adaptive IIR Filtering

Zheng

Qian

2022

Entropy

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Augmented IIR filter adaptive algorithms have been considered in many studies, which are suitable for proper and improper complex-valued signals. However, lots of augmented IIR filter adaptive algorithms are developed under the mean square error (MSE) criterion. It is an ideal optimality criterion under Gaussian noises but fails to model the behavior of non-Gaussian noise found in practice. Complex correntropy has shown robustness under non-Gaussian noises in the design of adaptive filters as a similarity measure for the complex random variables. In this paper, we propose a new augmented IIR filter adaptive algorithm based on the generalized maximum complex correntropy criterion (GMCCC-AIIR), which employs the complex generalized Gaussian density function as the kernel function. Stability analysis provides the bound of learning rate. Simulation results verify its superiority.

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Section: Introductionmentioning

confidence: 99%