Blind Volterra signal modeling

In this paper the problem of nonlinear signal modeling is examined from a higher-order statistical perspective. The approach taken involves the use of second order Volterra kernels which are derived from a joint operation on second and third order moments of the signal. The paper describes the fundamental issues of the various components of the approach. The nonlinear equations involved are solved by means of unconstrained Lagrange programming neural networks. The results of the entire modeling scheme contained in this paper are very encouraging