Extended Generalization of Fuzzy Rough Sets

This paper extends and generalizes the approximations of fuzzy rough sets dealing with fuzzy coverings of the universe induced by a weak fuzzy similarity relation. The weak fuzzy similarity relation is considered as a generalization of fuzzy similarity relation in representing a more realistic relationship between two objects in which it has weaker symmetric and transitive properties. Since the conditional symmetry in the weak fuzzy similarity relation is an asymmetric property, there are two distinct fuzzy similarity classes that provide two different fuzzy coverings. The generalization of fuzzy rough sets approximations is discussed based on two interpretations: object-oriented generalization and class-oriented generalization. More concepts of generalized fuzzy rough set approximations are introduced and defined, representing more alternatives to provide level-2 interval-valued fuzzy sets. Moreover, through combining several pairs of proposed approximations of the generalized fuzzy rough sets, it is possible to provide the level-2 type-2 fuzzy sets as an extension of the level-2 interval valued fuzzy sets. Some properties of the concepts are examined

Analysis of the Shufflenet with Different Contention Resolution Schemes

In our earlier study [1], we investigated the performance of a shufflenet with different control strategies using different buffer architectures and routing algorithms through simulation. In this paper, we present the analysis of the control strategies proposed in [1]. By modeling the system as a Markov process, the performance of the shufflenet can be derived through only one parameter -- the probability of deflection, P def , in the network. In the analysis of buffered shufflenet with two packet classes (i.e., "care" and "don't care" classes), the state space for the memory transition increases generally with the order of O(n 2 ), where n is the buffer size in each node in the network. However, by making use of the particular structure of the memory, we can reduce the state space to O(n), which greatly simplifies the analysis of a shufflenet. We show how the analysis can be applied to one of the control strategies, namely CS-2, which achieves the highest throughput among all the c..