2026-09-19T13:34:02Zhttps://ecommons.cornell.edu/server/oai/requestoai:ecommons.cornell.edu:1813/111572026-05-14T13:52:21Zcom_1813_35col_1813_47
Adams, Bryant
2008-07-27T00:55:51Z
2013-07-27T06:26:45Z
2008-07-27T00:55:51Z
https://hdl.handle.net/1813/11157
6397224
In 2007 Nerode introduced the notion of an update automaton and update transducer to model the evolution of interactions of arbitrary functions on arbitrary domains governed by a finite automaton. We show the scope of this methodology by modeling a variety of processes, including database networks, interactive proofs, finite-state transducers, and financial ledgers. We produce a novel solution method and associated transducers for finite systems of arbitrary-order non-homogeneous linear difference equations over a field using Hermite's unimodular polynomial matrix row reduction. These transducers can be viewed as time invariant linear causal maps of the linear space of sequences of vectors over the base field.
en_US
automata
transducers
state machines
difference equations
modeling
Representing processes as Update Automata and Transducers
dissertation or thesis
application/pdf
Publication
Cornell Theses and Dissertations
Adams, Bryant
5893a6ea-7af3-41d7-abc6-04bcd26ab5df
open.access
open.access
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<Abstract>In 2007 Nerode introduced the notion of an update automaton and update transducer to model the evolution of interactions of arbitrary functions on arbitrary domains governed by a finite automaton. We show the scope of this methodology by modeling a variety of processes, including database networks, interactive proofs, finite-state transducers, and financial ledgers. We produce a novel solution method and associated transducers for finite systems of arbitrary-order non-homogeneous linear difference equations over a field using Hermite's unimodular polynomial matrix row reduction. These transducers can be viewed as time invariant linear causal maps of the linear space of sequences of vectors over the base field.</Abstract>
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