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High Performance Implementation of Nested Array Beamformer for Wideband Radar Applications

2019· article· en· W3005045914 on OpenAlex
Mohammed Shoukry, Fayez Gebali, P. Agathoklis

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
FieldEngineering
TopicAntenna Design and Optimization
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsField-programmable gate arrayComputer scienceWidebandGate arrayElectronic engineeringRadarChipComputer hardwareEmbedded systemEngineeringTelecommunications

Abstract

fetched live from OpenAlex

Beamformer is an important part of the wideband radar systems. An approach to achieve the high sampling rate required in such systems is to use efficient hardware implementations. This paper presents a speed optimized systolic arrays for implementation of the wideband beamformer using nested arrays, 2-D filters, and multirate techniques. The implementation structures of the beamformer basic building blocks are designed based on systematic methodology and implemented using the field programmable gate array (FPGA) platform targeting Basys- 3 development board's Xilinx Artix-7 (XC7A100T) FPGA chip. A single channel of the beamformer was chosen for the implementation to confirm the correct functionality of the FPGA architecture. The implementation performance is tested in terms of effect of errors due to finite word-length arithmetic.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.812
Threshold uncertainty score0.200

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 communication0.0000.000
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 head0.006
GPT teacher head0.216
Teacher spread0.210 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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