Hardware Realization of Mixed-Signal Neural Networks with Modular Synapse-Neuron arrays
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, a mixed-signal current-mode structure of a feed-forward neural network is implemented. In this network, neurons are divided and distributed as sub-neurons into parallel elements composing unified synapse-neuron building blocks in combination with the synapses. Although in this brief paper a resistive sigmoidal neuron is considered, the neuron is adaptable to other forms of transfer functions. The synapse structure employs AND gates in addition to weighted current mirrors to reduce the area of the design. As a proof of concept, a 4-3-2 CMOS-based network is implemented. The average and maximum power consumptions of the network are 0.93mW and 5.81 mW respectively. The area of the entire network is measured 142299.5μm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . The network was successfully tested with a series of sample patterns.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it