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Record W2105118470 · doi:10.1109/ultsym.2002.1193373

A new SAW band reject filter and its applications in wireless systems

2003· article· en· W2105118470 on OpenAlexaff
S. Beaudin, Chunyun Jian, D. Sychaleun

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsHandsetISM bandWirelessComputer scienceResonatorInsertion lossBand-stop filterBase stationBand-pass filterElectronic engineeringPassbandElectrical engineeringTopology (electrical circuits)TelecommunicationsBandwidth (computing)EngineeringLow-pass filter

Abstract

fetched live from OpenAlex

SAW notch or band reject filters can achieve very low insertion losses and withstand very high powers in their pass bands. Despite these very promising attributes relatively little work has been invested to develop this technology, and of the little work which has been conducted, most of it focused on developing narrow band notch filters to suppress single tone carriers. The present paper introduces band reject filters constructed of single pole resonators in the well known ladder topology. The ability to reject a specific band while providing significantly less than 1 dB of insertion loss in the pass band make this technology very attractive for the front end of base station receivers or handset transmit or receive chains. The paper discusses the design methodology, highlight the performance of several prototype filters and discuss the numerous applications which we are currently considering for these components. It is our belief that such components will find many applications in RF design and open new markets for SAW technology in wireless systems.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score0.288

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 head0.011
GPT teacher head0.206
Teacher spread0.195 · 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 designTheoretical or conceptual
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

Citations6
Published2003
Admission routes1
Has abstractyes

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