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Record W2137701300 · doi:10.1109/acssc.1988.753975

Sensitivity Analysis Of 3-D Recursive Digital Beam Filter Structures

2005· article· en· W2137701300 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDigital Filter Design and Implementation
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSignal-flow graphQuantization (signal processing)Digital filterMultiplier (economics)ResistorNetwork synthesis filtersFilter (signal processing)Sensitivity (control systems)Computer scienceMathematicsSignal processingSIGNAL (programming language)AlgorithmElectronic engineeringControl theory (sociology)Topology (electrical circuits)Digital signal processingEngineeringElectrical engineeringArtificial intelligenceComputer hardware

Abstract

fetched live from OpenAlex

Three dimensional (3-D) recursive digital beam filters may be designed from 3-D inductor capacitor-resistor analog prototype networks. It is known that such filters may be realized as direct-form (DF) signal flow graphs or, as recently suggested, as wave digital (WD) signal flow graphs. The latter structures are known to be computationally less intensive. In this contribution, it is shown that the multiplier coefficient quantization errors are far less for 3-D WD filters compared with 3-D DF filters, thereby allowing much shorter wordlengths to be employed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.824
Threshold uncertainty score0.264

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 science0.0000.000
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 head0.019
GPT teacher head0.264
Teacher spread0.245 · 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

Citations6
Published2005
Admission routes1
Has abstractyes

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