Fuzzy decision diagrams for the representation, analysis, and optimization of rule bases

In this paper, a representation of multivalued functions called interval decision diagrams (IDDs) is introduced. It is related to similar representations such as binary decision diagrams. Compared to other functional representations with regard to symbolic formal verification approaches, IDDs show some important properties that enable us to verify process networks and related models of computation more adequately than with conventional approaches. Therefore, a new form of transition relation representation called interval mapping diagram (IMD) is introduced.A novel approach to symbolic model checking of process networks is presented. Several drawbacks of traditional strategies are avoided using IDDs and IMDs. The resulting transition relation IMD is very compact, enabling fast image computations. Furthermore, no artificial limitations concerning buffer capacities or equivalent have to be introduced. Additionally, applications concerning scheduling of process networks are feasible. IDDs and IMDs are defined, their properties are described, and computation methods and techniques are given.

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Fuzzy decision diagrams for the representation, analysis, and optimization of rule bases

Cited by 7 publications

References 25 publications

Introduction to Noise-Resilient Computing

Introduction to Noise-Resilient Computing

Conquering Uncertainty in Multiple-Valued Logic Design

Interval diagrams for efficient symbolic verification of process networks

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