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On the Scott-continuity of tagged signal processes

Laurent Moss and Guy Bois

Technical Report (2009)

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Cite this document: Moss, L. & Bois, G. (2009). On the Scott-continuity of tagged signal processes (Technical Report n° EPM-RT-2009-01).
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Abstract

Process networks are frequently used to model signal processing and multimedia applications. It is important to ensure that a process network has a uniquely defined behavior in order to correctly model such deterministic systems. Furthermore, a constructive procedure to determine this unique behavior is necessary for its simulation and execution. By the Kahn principle, the unique behavior of a process network is known to be the least fixed point of the network functional when every process computes a Scott-continuous function. The Kahn principle is used in a recent timed extension of the least fixed point semantics of Kahn process networks, using the tagged signal model. In this extension, processes compute a function from input signals to output signals, where a signal is defined as a partial function from a down set of tags to a set of values. However, it is often tedious to formally prove that a tagged signal process is Scott-continuous. This paper presents theorems on Scott-continuity that simplify such proofs. Thus, a general theorem on the necessary and sufficient conditions for the Scott-continuity of tagged signal processes is proven. Scott-continuity is then proven for broad classes of processes, namely the classes of exactly causal processes and of domain-warping processes, which include stateless processes, delays as well as a subset of discrete-event processes.

Uncontrolled Keywords

Process networks, Denotational semantics, Timed systems, Discrete events, Dataflow

Open Access document in PolyPublie
Subjects: 2700 Technologie de l'information > 2700 Technologie de l'information
2700 Technologie de l'information > 2719 Architecture d'ordinateur et conception
Department: Département de génie informatique et génie logiciel
Date Deposited: 06 Oct 2017 13:37
Last Modified: 24 Oct 2018 16:12
PolyPublie URL: https://publications.polymtl.ca/2640/

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