Identification of Volterra kernels using interpolation

The paper presents a new method for the identification of frequency-domain Volterra kernels. Based on the assumption that frequency-domain kernels are focally smooth, the kernel surface can be approximated by interpolation techniques, thus reducing the complexity of the model. Similarly to the unreduced (Volterra) model, this smaller model is also (i) linear in the unknowns, (ii) only locally sensitive to its parameters and (iii) free of structural assumptions about the system. The parameter estimation boils down to solving a linear system of equations in the least-squares (LS) sense. The design of the interpolation scheme is described, and the performance of the approximation is analyzed, and illustrated by simulation. The algorithm allows a significant saving in measurement time compared to other kernel estimation methods