FIR System Identification using a Linear Combination of Cumulants

In this paper we develop a general linear approach to identify the parameters of a moving average (MA) model from the statistics of the output. First, we show that, under some constraints, the impulse response of the system can be expressed as a linear combination of cumulant slices. Then, this result is used to obtain a new well-conditioned linear method to estimate the MA parameters of a non-gaussian process. The proposed approach does not require a previous estimation of the filter order. Simulation results show improvement in performance with respect to existing methods.