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Record W1564466119 · doi:10.1109/iscas.1999.780615

Design and switched-capacitor implementation of a new cascade-of-resonators Σ-Δ converter configuration

2003· article· en· W1564466119 on OpenAlexaff
Y. Botteron, B. Nowrouzian, A. T. FULLER

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCascadeIntegratorResonatorBand-pass filterDelta-sigma modulationRealization (probability)PhysicsCapacitorTopology (electrical circuits)Transfer functionSwitched capacitorElectronic engineeringSigmaControl theory (sociology)EngineeringComputer scienceElectrical engineeringVoltageMathematicsOptoelectronicsCMOS

Abstract

fetched live from OpenAlex

Recently, the authors combined the hitherto cascade-of-integrators and cascade-of-resonators /spl Sigma/-/spl Delta/ converter configurations into a single cascade-of-resonators bandpass /spl Sigma/-/spl Delta/ converter. The salient features of the resulting bandpass /spl Sigma/-/spl Delta/ converter configuration is that it leads to the realization of complementary signal and noise transfer functions while permitting the automatic placement of the noise transfer function zeros at real frequencies (i.e. on the unit-circle in the discrete-time z domain). This /spl Sigma/-/spl Delta/ converter configuration consists of one single-bit quantizer and N second-order resonators (N second-order resonators and 1 integrator, respectively), leading to the realization of an even 2N-th (an odd (2N+1)-th, respectively) order bandpass /spl Sigma/-/spl Delta/ converter. This paper is concerned with an investigation and Monte-Carlo simulation of the proposed cascade-of-resonators bandpass /spl Sigma/-/spl Delta/ converter configuration satisfying a practical set of design specifications for a corresponding hardware implementation using the switched-capacitor 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.940
Threshold uncertainty score0.405

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 head0.021
GPT teacher head0.241
Teacher spread0.220 · 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 designBench or experimental
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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