A CMOS current-mode PWM technique for analog neural network implementations
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Bibliographic record
Abstract
In this paper, a CMOS current-mode pulse width modulation (PWM) technique for efficiently implementing analog neural networks is presented. The weighted summation operation (required for a neural network) is realized by switching a weight current, controlled by a pulse whose width is proportional to an input current. This current is then applied to a resettable current integrator. The sigmoid transformation is naturally performed by the nonlinear transconductance amplifier which forms the integrator. This results in minimum silicon area and therefore is suitable for very large scale neural systems. Other pronounced features of the current-mode PWM technique are its easy programmability, electronically adjustable gains of neurons, and modular structures. In this paper, four modules are introduced with which almost all neural networks can be realized modularly. Simulations are provided to verify the validity of our proposed technique.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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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