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Record W2157665660 · doi:10.1109/tcomm.2010.10.080336

A Novel High Data Rate Modulation Scheme Based on Chaotic Signal Separation

2010· article· en· W2157665660 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.

Bibliographic record

VenueIEEE Transactions on Communications · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicChaos control and synchronization
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAdditive white Gaussian noiseComputer scienceChaoticTransmission (telecommunications)Modulation (music)Channel (broadcasting)Electronic engineeringGaussian noiseSIGNAL (programming language)Data transmissionNoise (video)Signal-to-noise ratio (imaging)AlgorithmTelecommunicationsComputer networkEngineeringArtificial intelligenceAcousticsPhysics

Abstract

fetched live from OpenAlex

Based on separation of the sum of chaotic signals, this paper proposes a novel spread spectrum modulation scheme-initial condition modulation (ICM), which is suitable for high data rate communications. The success of signal separation makes it possible to transmit multiple information streams through single channel. This technique significantly improves data transmission rate and implies good information security. Our theoretical analysis shows that this approach can also cleanse the additive white Gaussian noise imposed by communication channel. Computer simulations confirm that the proposed method has a good noise performance.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.973
Threshold uncertainty score0.760

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.297
Teacher spread0.256 · 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