GENERALIZED ORTHONORMAL BASIS SELECTION FOR EXPANDING QUADRATIC VOLTERRA FILTERS

摘要

Volterra models are very useful for signal and system representation due to their general non-linear structure and their property of linearity with respect to the kernels coefficients. However, when using such models we are confronted with a complexity problem that results from the very large number of the kernels coefficients. Expanding the kernels on a generalized orthonormal basis allows to significantly reduce this parametric complexity. In the present paper, a new procedure is proposed for selecting such a generalized orthonormal basis so that a least squares criterion is minimized in the case of a homogeneous quadratic model.