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Record W4300424340 · doi:10.48550/arxiv.1801.08704

Event-triggered stabilization of disturbed linear systems over digital\n channels

2018· preprint· en· W4300424340 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuearXiv (Cornell University) · 2018
Typepreprint
Languageen
FieldComputer Science
TopicNetwork Time Synchronization Technologies
Canadian institutionsUniversity of Regina
FundersNational Science Foundation
KeywordsBounded functionControl theory (sociology)Inverted pendulumTransmission (telecommunications)Channel (broadcasting)Computer scienceScalar (mathematics)Network packetLinear systemDecoding methodsMathematicsAlgorithmControl (management)TelecommunicationsNonlinear systemPhysicsComputer networkMathematical analysis

Abstract

fetched live from OpenAlex

We present an event-triggered control strategy for stabilizing a scalar,\ncontinuous-time, time-invariant, linear system over a digital communication\nchannel having bounded delay, and in the presence of bounded system\ndisturbance. We propose an encoding-decoding scheme, and determine lower bounds\non the packet size and on the information transmission rate which are\nsufficient for stabilization. We show that for small values of the delay, the\ntiming information implicit in the triggering events is enough to stabilize the\nsystem with any positive rate. In contrast, when the delay increases beyond a\ncritical threshold, the timing information alone is not enough to stabilize the\nsystem and the transmission rate begins to increase. Finally, large values of\nthe delay require transmission rates higher than what prescribed by the classic\ndata-rate theorem. The results are numerically validated using a linearized\nmodel of an inverted pendulum.\n

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.885
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.042
GPT teacher head0.188
Teacher spread0.146 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it