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Record W1584108841 · doi:10.1109/iscas.2006.1693736

Single-chip FPGA architecture for 3D IIR broadband spatio-temporal beam plane-wave filters

2006· article· en· W1584108841 on OpenAlexaff
Arjuna Madanayake, L.T. Bruton

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDigital Filter Design and Implementation
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBroadbandField-programmable gate arrayComputer scienceInfinite impulse responseFilter (signal processing)Frame rateElectronic engineeringMultiplexingFrame (networking)Computer hardwareAcousticsDigital filterTelecommunicationsEngineeringPhysicsArtificial intelligenceComputer vision

Abstract

fetched live from OpenAlex

A highly-directional FPGA-based broadband beam former is proposed using a novel 3D IIR plane-wave digital filter. This filter acquires the 3D spatio-temporal input signals from spatially-rectangular arrays of sensors that are scanned by only one time-multiplexed A/D converter. The proposed architecture employs a novel scanned-array 3D parallel vector-processor (VP), clocked at 80 MHz, and has the potential to achieve real-time broadband plane-wave filtering on a single low-cost integrated circuit at spatial frame-rates of 19 kHz over a 64 by 64 spatial broadband sensor array.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.036
GPT teacher head0.240
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations1
Published2006
Admission routes1
Has abstractyes

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