Digital LIF Neuron for CTT-Based Neuromorphic Systems
Why this work is in the frame
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Bibliographic record
Abstract
In this work, a novel digital leaky integrate-and-fire neuron design is proposed as part of a charge-trap transistor (CTT)-based neuromorphic system. CTTs, which are compute-in-memory devices, are used to realize the synaptic array of the neuron and support weight multiplication operations for incoming pulse signals. The proposed digital neuron does not rely on a capacitor for accumulation, making it area-efficient and scalable, and thus useful for design of large spiking neural networks. The neuron accumulates the weighted inputs from the synaptic array and generates an outgoing pulse, i.e., fires, when a pre-set threshold is reached. The digital neuron includes a sampler circuit, multi-level comparator, pulse generator, leaky circuit, 3-bit counter, and digital comparator circuit. Since the circuit is digital, the design is robust to noise, mismatch, and process, voltage, and temperature variations. The digital neuron is designed in GF 22 nm FDSOI technology, operates at a supply voltage of 0.8 V, and occupies an area of 33.5 μ m2. The neuron was simulated, including under temperature and supply voltage variations, and exhibits expected functionality.
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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