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Record W2108216980 · doi:10.1109/tcsi.2008.925364

On the Design of Undersampling Continuous-Time Bandpass Delta–Sigma Modulators for Gigahertz Frequency A/D Conversion

2008· article· en· W2108216980 on OpenAlexafffund
Ali Naderi, Mohamad Sawan, Yvon Savaria

Bibliographic record

VenueIEEE Transactions on Circuits and Systems I Regular Papers · 2008
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsPolytechnique Montréal
FundersCMC Microsystems
KeywordsUndersamplingDelta-sigma modulationElectronic engineeringBand-pass filterOversamplingCMOSSpurious relationshipBandwidth (computing)Spurious-free dynamic rangeComputer scienceSampling (signal processing)SIGNAL (programming language)EngineeringTelecommunications

Abstract

fetched live from OpenAlex

This paper describes issues and tradeoffs related to the design of undersampling delta-sigma modulators (DeltaSigmaMs) for wireless receivers. It proposes a new bandpass undersampling DeltaSigmaM architecture dedicated to multigigahertz frequencies. This paper is based on up-sampling in the feedback path to remove the analog mixer usually found in the modulator. Design equations are discussed for an optimum operating point when the input signal is at 1.8 GHz. The related design model can be applied to many communication standards. The underlying proposed architecture can receive high-frequency carriers modulated with signals of bandwidth as large as 5 MHz. In the proposed design, it converts the signal into digital data with a spurious-free dynamic range of 46 dB at a sampling frequency of 810.1 MHz. Design simulation, characterization, and implementation of the proposed modulator are done using a 0.13- mum CMOS technology.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.957
Threshold uncertainty score0.929

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 head0.028
GPT teacher head0.192
Teacher spread0.165 · 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 designSimulation or modeling
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

Citations19
Published2008
Admission routes2
Has abstractyes

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