A Low Voltage CMOS Multiplier for High Frequency Equalization
Bibliographic record
Abstract
This paper describes the design of a low power 1.2V CMOS multiplier for 10 Gbit/s continuous time finite impulse response (FIR) filter. The multiplier is based on a low noise amplifier (LNA) architecture and has variable gain, which is directly controlled by a 5 bit digital word. This direct control removes the need for a digital to analog converter to set the gain of the multiplier. The 5 bit control word allows 32 possible gain settings from a minimum gain of -1 to a maximum gain +1 with linearity errors less than 1%. The gain is achieved by switching in various combinations of binary weighted gain stages. To achieve negative gain, a swap switch is used which reduces the number of gain stages required and also reduces the parasitic load on the summing node. The circuit requires 1.9 mA of current and has a post-extracted bandwidth of 7.6 GHz.
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How this classification was reachedexpand
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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".