A constrained optimisation approach to the blind estimation of Volterra kernels

A novel approach is taken for the estimation of the parameters of a Volterra model, which is based on constrained optimisation. The equations required for the determination of the Volterra kernels are formed entirely from the second and higher order statistical properties of the “output” signal to be modelled and can therefore be classed as blind in nature. These equations are highly nonlinear and their solution is achieved through a judicious use of reliably measured statistical features of the signal to be modelled, in conjunction with appropriate constraints and penalty functions. Examples are given to illustrate the method and it is evident from those that this novel approach is producing useful results in contexts that have been hitherto unattainable