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Refinement for Signal Flow Graphs.

Authors: Filippo Bonchi; Joshua Holland; Dusko Pavlovic; Pawel Sobocinski 0001;

Refinement for Signal Flow Graphs.

Abstract

The symmetric monoidal theory of Interacting Hopf Algebras provides a sound and complete axiomatisation for linear relations over a given field. As is the case for ordinary relations, linear relations have a natural order that coincides with inclusion. In this paper, we give a presentation for this ordering by extending the theory of Interacting Hopf Algebras with a single additional inequation. We show that the extended theory gives rise to an abelian bicategory—a concept due to Carboni and Walters—and highlight similarities with the algebra of relations. Most importantly, the ordering leads to a well-behaved notion of refinement for signal flow graphs.

Countries
Italy, Germany
Keywords

000 Computer science, knowledge, general works, Computer Science, operational semantics, symmetric monoidal inequality theory, Signal flow graphs, refinement, string diagrams, Operational semantics; Refinement; Signal flow graphs; String diagrams; Symmetric monoidal inequality theory; Software, 004, 510

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green