An RBFNWiener hybrid filter using higher order signal statistics
In this paper we propose a radial basis function network (RBFN) based nonlinear filter with a basic framework of a linear Wiener filter. In addition, in order to improve the filtering performance, we further propose a novel nonlinear filter, which is synthesized by a hybridization of an RBFN filter and a linear Wiener filter. The proposed filters are realized with a least mean square error scheme using higher order statistics of a target signal and an observation noise. The validity and the effectiveness of the proposed filters have been verified by applying them to the actual filtering problems of the noisy images.
radial basis function network wiener filter least mean square error higher order statistics statistical independence