Cumulant based identification of multichannel moving-average models

Given cumulants of a stationary, perhaps noisy, non-Gaussian r-variate moving-average, MA(q) process, the authors study identifiability conditions, 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 less restrictions than that corresponding to a given covariance structure. The authors derive two algorithms for estimating the (possibly) nonminimum-phase MA coefficient matrices.