We consider a commutative ring $R$ with identity and a positive integer $N$. We characterize all the 3-tuples $(L_1,L_2,L_3)$ of linear transforms over $R^N$, having the “circular convolution” property, i.eṡuch that $x*y=L_3(L_1\left(x\right)\otimes L_2\left(y\right))$ for all $x,y\in R^N$.

This paper proposes a nonlinear regression structure comprising a wavelet network and a linear term. The introduction of the linear term is aimed at providing a more parsimonious interpolation in high-dimensional spaces when the modelling samples are sparse. A constructive procedure for building such structures, termed linear-wavelet networks, is described. For illustration, the proposed procedure is employed in the framework of dynamic system identification. In an example involving a simulated...