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Record W2142471239 · doi:10.1109/isimp.2004.1434001

Chaotic signal driven parametric modulation

2005· article· en· W2142471239 on OpenAlexaff
Hon Keung Kwan, Weiyi Tang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicChaos control and synchronization
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsSawtooth waveControl theory (sociology)ChaoticComputer scienceNonlinear filterKernel adaptive filterAdaptive filterRoot-raised-cosine filterFilter (signal processing)SIGNAL (programming language)Parametric statisticsDigital filterFilter designAlgorithmMathematicsTelecommunicationsArtificial intelligence

Abstract

fetched live from OpenAlex

A parametric modulated communication system driven by a chaotic signal is presented. The chaotic signal is generated by a chaotic digital filter with a sawtooth nonlinearity. In the system, an analysis-synthesis digital filter-pair, each with a sawtooth nonlinearity, consisting of one or more parametric modulated signals, is used. An adaptive modified Kalman filter or an adaptive modified NLMS filter can be used in the receiver to decode the transmitted signals. Simulations show that the system is able to transmit multiple signals over a Gaussian channel. Further, the study has been extended to include the uses of a pole-zero filter-pair and a second-order Volterra filter-pair, and their results are given.

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 score0.846
Threshold uncertainty score0.998

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)0.0030.000

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 head0.008
GPT teacher head0.215
Teacher spread0.208 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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