Kernel methods have emerged as a powerful tool in adaptive filtering and system identification, enabling the processing and modelling of complex, nonlinear relationships in dynamic systems. By mapping ...
This paper compares the method of Tikhonov regularization as advanced in 1963 with the more recent approach utilizing the theory of reproducing kernel Hilbert spaces (RKHS). The methods are shown to ...
Transformations of a class of Gaussian processes to the Brownian motion are obtained by reproducing kernel Hilbert space methods. These transformations are such that the value of the transformed ...
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