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Record W7096117533

Approved for Public Release Distribution Unlimited

2001· article· en· W7096117533 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDigital Filter Design and Implementation
Canadian institutionsnot available
Fundersnot available
KeywordsInfinite impulse responseTestbedCommunications satelliteFinite impulse responseDigital filterFilter (signal processing)MicroprocessorDigital signal processingSoftware
DOInot available

Abstract

fetched live from OpenAlex

Sa majeste " la reine, representee par le ministre de la Defense nationale, 2001 The work presented in this document contributes to the ROBR (Reconfigurable Omni Band Radio) project started by the Defence Research Establishment Ottawa and the Communication Research Centre in 1997. ROBR is a testbed implementation of a reconfigurable satellite communications (satcom) terminal that makes use of a software communications architecture. Such a system can enable the use of a single ground terminal to communicate over multiple satellite communications or terrestrial links by supporting multiple standards. The ROBR hardware architecture includes a microprocessor and several digital signal processor (DSP) boards. The objective of this report is to document the work done to provide a set of reconfigurable digital filters for use in the ROBR. Five infinite impulse response (IIR) filtering modules and four finite impulse response (FIR) filtering modules have been implemented. The function of these modules is to compute the coefficients of a desired filter design. Also, IIR and FIR signal processing modules have been implemented to process digital signals using the computed coefficients. The modules have

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.

How this classification was reachedexpand

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.973
Threshold uncertainty score0.316

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.068
GPT teacher head0.276
Teacher spread0.208 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2001
Admission routes1
Has abstractyes

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