Probability Models with Discrete and Continuous Parts

Probability Distributions: Discrete vs. Continuous

Approximating discrete probability distributions with decomposable models

A heuristic procedure is presented to approximate an 71dimensional discrete probability distribution with a decomposable model of a given complexity. It is shown that, without loss of generality, the search space can be restricted to a suitable subclass of decomposable models, whose members are called elementary models. The selected elementary model is constructed in an incremental manner accor...

Interaction of Discrete and Continuous parts of aBatch Process

Through a study taking past Computer-Integrated Manufacturing (CIM) experiences, and the ISA 5] and NAMUR 7] references into account, we tried to see how far techniques developed in the eld of Discrete Manufacturing Systems (DMS) could be extended to Batch Chemical Processes 1]. As a result, a distributed hierarchical control system has been built. The proposed supervisory control system is com...

Combining Discrete and Continuous Process Models

Two notions of process have been used in programs that reason about change* discrete models, which represent changes as instantaneous, and continuous models, which represent changes as processes that act gradually over time. We describe a technique called aggregation which unifies the two types of models and allows both to be used when performing qualitative simulation. Aggregation is a techniq...

Models of Continuous and Discrete Dynamical Systems

The authors have introduced in [KSW97a], KSW97b] two complementary algebras for systems with boundaries. The first is loops in the suspension of a monoidal category ⊗) , (C , denoted ⊗)) , ( Σ ( Ω C , an algebra of deterministic systems in which the natural feedback operation has delay. The second is Span(Graph), an algebra of specifications of systems (nondeterministic transition systems), w...