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Record W2115861312 · doi:10.1109/iscas.1993.394263

Analog neural network building blocks based on current mode subthreshold operation

2002· article· en· W2115861312 on OpenAlexaff
Liyan Song, M.I. Elmasry, Anthony Vannelli

Bibliographic record

Venue1993 IEEE International Symposium on Circuits and Systems · 2002
Typearticle
Languageen
FieldComputer Science
TopicNeural Networks and Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSubthreshold conductionArtificial neural networkComparatorComputer scienceElectronic engineeringCurrent (fluid)Analog signalAnalog signal processingAmplifierOperational amplifierElectronic circuitMultiplier (economics)Field-programmable analog arrayAnalogue electronicsFeed forwardElectrical engineeringAnalog multiplierTransistorArtificial intelligenceCMOSVoltageEngineeringComputer hardwareControl engineeringDigital signal processing

Abstract

fetched live from OpenAlex

A class of analog circuit building blocks for neural network implementation is presented which is based on the current mode subthreshold operation. This class of circuits includes current inverter, current-current multiplier, current amplifier and current comparator. A feedforward network with learning constructed by these building blocks was verified. These building blocks can be applied to artificial neural network (ANN) design in particular and to analog signal processing in general.>

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.042
GPT teacher head0.280
Teacher spread0.238 · 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 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

Citations10
Published2002
Admission routes1
Has abstractyes

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