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We develop a kernel adaptive filter for quaternion data based on maximizing correntropy. We apply a modified form of the HR calculus that is applicable to Hilbert spaces for evaluating the cost function gradient to develop the quaternion kernel maximum correntropy (KMC) algorithm. The KMC method uses correntropy to measure similarity between the filter output and the desired response. Here, the approach...
Nonlinear adaptive filters are getting more common and are useful especially where performance of linear adaptive filters may be unacceptable. Such areas include communications, image processing and biological systems. Quaternion valued data has also been drawing recent interest in various areas of statistical signal processing, including adaptive filtering, image pattern recognition, and modeling...
A recent paper titled “The Complex Gaussian Kernel LMS Algorithm” published by Bouboulis and Theodoridis introduced a complex version of the Gaussian kernel LMS (KLMS) algorithm. In this paper, we extend the concepts of complex and complexified RKHS spaces to develop suitable complex Kernel based adaptive algorithms using the Affine projection algorithm (KAPA) method. We apply the complex Gaussian...
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