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Robust augmented Volterra adaptive filtering
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AI
DOI：10.1016/j.sigpro.2024.109573.png)
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Abstract
En 中文
In the field of nonlinear signal processing, Volterra filter is generally used as an effective tool. The utilization of the augmented model can make the filter maintain its merit in both circular and non -circular signals. From this point of view, this paper proposes a new online nonlinear system model called the augmented Volterra model. To combat impulsive noise, we introduce the complex correntropy to the Volterra filter, and propose the augmented Volterra recursive maximum complex correntropy criterion (A-VRMCCC) algorithm. Considering the computational cost of the augmented Volterra model, we propose the decomposable method to effectively reduce its computational load. Additionally, the performance of A-VRMCCC has also been studied. Finally, simulation results validate the correctness of the performance analysis, and show that the newly proposed algorithms have a competitive advantage over other algorithms.
Keywords:
Volterra
Augmented
Decomposable
Complex correntropy
Robustness