Linear prediction based on higher order statistics by a new criterion

This criterion requires only partial Mth-order cumulants C_M,e(0,k₁, k₁, . . ., k_M/2-1, k _{M /2-1}) of the prediction error e(k ) where M is even. Theoretically, it is shown that the proposed filter associated with a stationary process x(k ) is the same as the conventional correlation based (minimum-phase) LPE filter associated with the nonGaussian signal y(k) (noise-free). Simulation results show that when y(k) is an autoregressive process of known order, the proposed filter works well