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A Kernel Affine Projection-Like Algorithm in Reproducing Kernel Hilbert Space
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DOI：10.1109/TCSII.2019.2947317.png)
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Abstract
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A kernel affine projection-like algorithm (KAPLA) is proposed in reproducing kernel Hilbert space in non-Gaussian environments. The cost function for the developed algorithm is constructed by using the correntropy approach and Gaussian kernel to deal with nonlinear channel estimation. The devised algorithm can efficiently operate in the impulse noise. As a consequence, the proposed KAPLA algorithm provides good performance for nonlinear channel equalization in impluse-noise environments. Simulations results in different mixed noise environments verify the superior behavior of KAPLA compared to known algorithms.
Keywords:
Kernel
Signal processing algorithms
Hilbert space
Circuits and systems
Cost function
Channel estimation
Simulation
Correntropy
kernel affine projection-like algorithm
non-Gaussian environments
reproducing kernel Hilbert space
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