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Record W2169850495 · doi:10.1109/mwscas.2009.5235893

A power-efficient, high data rate chaos-based Transceiver design

2009· article· en· W2169850495 on OpenAlexaff
Deyasini Majumdar, Henry Leung, Brent Maundy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicChaos control and synchronization
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsTransceiverCHAOS (operating system)Computer scienceChaoticErgodic theoryPower (physics)High data rateModulation (music)Electronic engineeringWirelessEngineeringMathematicsTelecommunications

Abstract

fetched live from OpenAlex

Chaos-based schemes to date have failed to offer supportable data rates of the order of Mbps. This paper presents the design and verification of a high data rate (order of Mbps) chaos-based transceiver system based on the ergodic chaotic parameter modulation (ECPM) scheme. In evaluating the data rate of the proposed transceiver, a novel technique to analyze the maximum theoretical data rate capability of any given communication scheme has been devised. The practically achieved value, as obtained from experiments, has been found to be close to the theoretical counterparts. Further, it has been observed that the proposed design is power and resource efficient as compared to existing conventional counterparts.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score0.999

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)0.0020.000

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 head0.022
GPT teacher head0.243
Teacher spread0.222 · 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.

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

Citations1
Published2009
Admission routes1
Has abstractyes

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