In this paper we study the separability in the plane by two criteria: double wedge separability and constant turn separability. We give O(N logN)-time optimal algorithms for computing all the separating double wedges of two disjoint sets of objects (points, segments, polygons and circles) and the flattest minimal constant turn polygonal line separating two sets of points.

This paper addresses arguments that “separability” is an assumption of Bell’s theorem, and that abandoning this assumption in our interpretation of quantum mechanics (a position sometimes referred to as “holism”) will allow us to restore a satisfying locality principle. Separability here means that all events associated to the union of some set of disjoint regions are combinations of events ass...

Measures of class separability can provide valuable insights into data, and suggest promising classification algorithms and approaches in data mining. We compare three simple class separability measures used in supervised machine learning. Their relative effectiveness is evaluated through their functional relationships and their random projections of data onto R for visualization. We conclude t...

We investigate the separability of arbitrary n-dimensional multipartite identical bosonic systems. An explicit relation between the dimension and the separability is presented. In particular, for n = 3, it is shown that the property of PPT (positive partial transpose) and the separability are equivalent for tripartite systems.

Geometric separability is a generalisation of linear separability, familiar to many from Minsky and Papert’s analysis of the Perceptron learning method. The concept forms a novel dimension along which to conceptualise learning methods. The present paper shows how geometric separability can be defined and demonstrates that it accurately predicts the performance of a at least one empirical learni...

The separability of a resistor-inductorcapacitor-mutual inductance (RLCM) network is defined in this paper. Some separability, reducibility and controllability (observability) criteria of RLCM networks over ( ) F z are derived. Two illustrative examples are given. Index Term—RLCM Networks, Separability, Reducibility, Controllability