Separability of signal mixtures given only one mixture observation is defined as the identification of the accuracy to which the signals can be separated. The paper shows that when signals are separated using the generalised Wiener filter, thedegree of separability can be deduced from the filter structure. To identify this structure, the processes are represented on an arbitrary spectral domain, and a sufficient solution to the Wiener filter is obtained. The filter is composed of a termindependent of the signal values, corresponding to regions in the spectral domain where the desired signal components are not distorted by interfering noise components, and a term dependent on the signal correlations, corresponding to the region wherecomponents overlap. An example of determining perfect separability of modulated random signals is given.
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