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Unlike the Schetzen method, this identification method proposed can process inputs with discrete distribution, accepts kernels of any length, tolerates signal-independent zero-mean additive noise irrespective of its color and distribution, and leads to a closed form solution. Identifiability is proved under assumptions on input moments; more accurate conditions are derived for particular discrete inputs (in particular in the complex plane, distributions symmetric about both axes). Several simulations demonstrate its efficiency and its speed for various discrete input distributions.