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Record W2133785369 · doi:10.1109/pacrim.1989.48367

Orthogonal phase functions for full response noncoherent CPM systems

2003· article· en· W2133785369 on OpenAlexaff
Rashmi Pandey, H. Leib, S. Pasupathy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicBlind Source Separation Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFrequency-shift keyingContinuous phase modulationOrthogonalityDemodulationModulation indexModulation (music)Phase (matter)Function (biology)Phase modulationAlgorithmComputer scienceMathematicsElectronic engineeringTopology (electrical circuits)Control theory (sociology)TelecommunicationsEngineeringChannel (broadcasting)AcousticsControl (management)PhysicsElectrical engineeringArtificial intelligencePulse-width modulationCombinatorics

Abstract

fetched live from OpenAlex

Continuous phase modulation (CPM) with noncoherent detection over a one-symbol interval is discussed. In order to obtain good performance with this simple demodulation strategy, the phase function of the modulation scheme has to be designed properly. An approach to shaping the purchase function to achieve noncoherent orthogonal performance for various values of the modulation index (h) is presented. Using the Gram-Schmidt orthogonality procedure, an entire family of orthogonal phase functions for h>or=0.68 is derived. All CPM schemes with these phase functions produce the same performance as noncoherent orthogonal signaling. For h=1 the phase function reduces to that of the FSK phase function. It is shown that there are CPM schemes that give the same SNR performance as noncoherent orthogonal FSK but have some spectral advantages over the FSK modulation format.>

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.034
GPT teacher head0.320
Teacher spread0.286 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2003
Admission routes1
Has abstractyes

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