Convex combination of spline adaptive filters
In this paper, we propose an adaptive and convex combination of a recent class of nonlinear adaptive filters in different configurations. The proposed architecture relies on the properties of the adaptive combination of filters which exploits the capabilities of different constituents, thus adaptively providing at least the behavior of the best performing filter. The nonlinear functions involved in the adaptation process are based on spline function interpolation and their shapes can be modified during learning using gradient-based techniques.