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Simplified Set-Membership Augmented Affine Projection Generalized Maximum Complex Correntropy Criterion Algorithm
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AI
DOI：10.1109/TCSII.2024.3365212.png)
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Abstract
En 中文
In order to cope with the situation, the performance of the set-membership augmented affine projection algorithm deteriorates dramatically when the output signal contains impact noise, this brief applies the maximum complex correntropy criterion to the set-membership augmented affine projection algorithm. And since the maximum complex correntropy criterion is robust, it can enhance the ability of the algorithm to resist impact noise. Then to better deal with the problems caused by strongly correlated input signals, the simplified set-membership augmented affine projection maximum complex correntropy algorithm (SSM-AAPMC) is proposed in this brief. To extend the algorithm to a more general form, the simplified set-membership augmented affine projection generalized maximum complex correntropy algorithm (SSM-AAPGMC) is derived. Furthermore, the stability of the proposed algorithm as well as the computational complexity between the proposed and other algorithms are analyzed. Finally, the simulation results confirm that the proposed two algorithms can maintain good performance under impact noise.
Keywords:
Signal processing algorithms
Cost function
Computational complexity
Random variables
Kernel
Filtering algorithms
Computational efficiency
Affine projection
maximum complex correntropy
set-membership
Journal
I
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4.9
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8.8K
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2.5W