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Record W2803085185 · doi:10.1049/el.2018.1103

Time‐domain approach for LFM signal parameter estimation based on FPGA

2018· article· en· W2803085185 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueElectronics Letters · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced Electrical Measurement Techniques
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersFundamental Research Funds for the Central UniversitiesUniversity of Electronic Science and Technology of ChinaUniversity of British Columbia
KeywordsField-programmable gate arrayTime domainSIGNAL (programming language)Computer scienceEstimationElectronic engineeringFrequency domainSignal processingEngineeringEmbedded systemComputer hardwareDigital signal processingSystems engineering

Abstract

fetched live from OpenAlex

An FPGA‐based parameter estimation method for linear frequency modulation (LFM) signal is proposed. The average frequency value of basic time slice is obtained by using improved time‐domain counting method. Then, frequency values are used for the least‐squares fitting, so as to obtain the sweep rate of LFM signal. Compared to estimation methods based on digital signal processing, the proposed approach can effectively reduce the estimation time. Experimental results show that the slope fitting accuracy of mono‐component LFM signal is better than 99.8% and the processing time is <250 ns.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.655
Threshold uncertainty score0.853

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 head0.010
GPT teacher head0.225
Teacher spread0.215 · 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