The linear discriminant analysis is an alternative which is optimized for class separability. It is a measure deriving from the PPT criterion for separability. In Euclidean geometry, linear separability is a property of two sets of points. It shows that separability does not inherit to closed subspaces. The concept of separability of a stochastic process was introduced by Joseph Doob. The scheduling of receivers with different spatial signatures allows good separability. One important debate exists within legal positivism about the separability of law and morality. A separability idempotent is given by formula 20. In particular, this shows that separability idempotents need not be unique. This property can also be called locality or separability. He wrote on valuation rings and Witt vectors, and separability in infinite field extensions. It is not, however, optimized for class separability. A number of indicators of approximate separability can be used, see Golyandina et al. The perfect closure can be used in a test for separability. There are still currently opposing articles of the separability of the process underlying these concepts.