Cumulant based identification of multichannel moving-average models

Given cumulants of a stationary, perhaps noisy, non-Gaussian r-variate moving average, MA(q) process, identifiability conditions are studied, under which the MA coefficient matrices, the input statistics, and the order q can be uniquely determined. The selection of a unique representative from the equivalence class corresponding to a given cumulant structure involves fewer restrictions than that corresponding to a given covariance structure. Two algorithms are derived for estimating the (possibly) nonminimum-phase MA coefficient matrices.<
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