Identification of the Volterra kernels of a process containing single-valued nonlinearities

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Abstract
An analysis is presented that shows how the Volterra kernels of a continuous single-valued nonlinear process may be identified from measured harmonic frequency-response data. The analysis facilitates the systematic formulation of identification equations for nonlinearities, which can be approximated by power series, without restricting the order of the approximation.