This paper introduces a neural network architecture based on rough sets and rough membership functions. The neurons of such networks instantiate approximate reasoning in assessing ...
James F. Peters, Andrzej Skowron, Liting Han, Shee...
This paper introduces the design of rough neurons based on rough sets. Rough neurons instantiate approximate reasoning in assessing knowledge gleaned from input data. Each neuron c...
James F. Peters, Andrzej Skowron, Zbigniew Suraj, ...
Using concepts from rough set theory we investigate the existence of approximative descriptions of collections of objects that can be extracted from data sets, a problem of intere...
Abstract. Subsystem based generalizations of rough set approximations are investigated. Instead of using an equivalence relation, an arbitrary binary relation is used to construct ...