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Record W2389446299

The Implementation of High Speed Slant-range Calculation in Synthetic Aperture Sonar with FPGA

2009· article· en· W2389446299 on OpenAlexvenueno aff
Zhang Chun-hua

Bibliographic record

VenueMicrocomputer applications · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsnot available
Fundersnot available
KeywordsField-programmable gate arrayComputer scienceRange (aeronautics)Economic shortageComputer hardwarePixelSynthetic aperture sonarSonarAlgorithmReal-time computingComputer visionArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

Calculate the slant-range between receiving transducer and imaging pixel is an important ste Pin time-domain imaging algorithm of synthetic aperture sonar(SAS).Two square,one addition and one square root operations is used.So look-u Ptable is mostly used instead of real-time calculation in real-time SAS imaging algorithm because of its high computational complexity.The shortage is inaccuracy and heavy memory and Front Side Bus(FSB)resources occupation.A method of single precision high speed slant-range calculation using Field Programmable Gate Array(FPGA)is brought out in this paper.The results of experiment show that the speed of 413.4M times per second is achieved in a single thread using tiny resources of FPGA,which is much faster than general purpose processor.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.924
Threshold uncertainty score0.221

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 head0.009
GPT teacher head0.252
Teacher spread0.243 · 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 designObservational
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

Citations0
Published2009
Admission routes1
Has abstractyes

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