On a new topology for the transconductance feedback amplifier
Bibliographic record
Abstract
A new topology for a transconductance feedback amplifier (TFA) is presented in this paper. The topology offers the advantage that it is capable of realizing the negative of the standard inverting gain expression. That is, gains of the form +R/sub 2//R/sub 1/. We will also show that it can realize the standard inverting and noninverting gains, all the while maintaining near constant bandwidth in each configuration as gain is varied. This first feature makes the proposed topology attractive for filtering applications since the TFA can function as an integrator, thereby allowing this amplifier to realize positive and negative lossless integrators. The proposed amplifier can also generate the logarithm of an input in the first and fourth quadrants, unlike previous TFA configurations. The proposed amplifier was verified experimentally for different gain configurations, integration and logarithmic capabilities by a chip designed using TSMC's 0.18-/spl mu/m CMOS process of a single ended power supply of 1.8 V. The chip occupied an area of 752.6 /spl mu/m by 581.2 /spl mu/m and contained the proposed amplifier and a conventional TFA for comparison purposes. A bandwidth of 15 MHz was observed for the proposed TFA in the unity gain (/spl plusmn/1) configuration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
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 source (direct Gemma or distilled Codex), 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".