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Estimating Poles of Motion Systems from Output-Only Measurements Using Generalized Transmissibility Operators

2025· article· W7123360826 on OpenAlex

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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

Venuenot available
Typearticle
Language
FieldEngineering
TopicControl Systems and Identification
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsTransmissibility (structural dynamics)Dimension (graph theory)Mathematical modelConstruct (python library)Control theory (sociology)Motion (physics)

Abstract

fetched live from OpenAlex

Transmissibility operators are mathematical objects that relate two subsets of outputs of a dynamic system. Transmissibility operators are used in applications where the dynamics of the underlying system and the input excitation are not available. Therefore, output measurements collected using sensors, which represent the only available information about the dynamic system in this case, can be used to identify transmissibility operators. Generalized transmissibility operators, which have been recently introduced, provide a more general mathematical characterization of transmissibility operators by relaxing an assumption that requires knowledge of the dimension of the excitation signal to construct meaningful transmissibility operators. Although generalized transmissibility operators are constructed from the zeros of the underlying system and not the poles, we show in this paper that the determinant of the difference between two generalized transmissibility operators constructed between the same outputs but under different input locations can be used to determine the poles of the underlying system. We apply the proposed approach to determine the poles of a motion system from two transmissibility operators.

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)0.001
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: Empirical
Teacher disagreement score0.484
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.046
GPT teacher head0.275
Teacher spread0.228 · 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

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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