A RISC architecture for 2DLNS-based signal processing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The multi-dimensional logarithmic number system (MDLNS) provides a reduction in the size of the number representation and promises a lower cost realisation of arithmetic operations. The non-linear nature of the representation and independency of the parallel-based computations combined with multi-digit extensions of the MDLNS representations along with simplified arithmetic operations, make MDLNS suitable for some multiplication intensive DSP applications. The work presented in this paper is the design and implementation of a 2DLNS-based processor architecture. This CPU takes advantage of a relatively simple architecture and a well designed organisation which greatly improves the implementation of many DSP algorithms. An assembly programme is also written to implement a 2DLNS-based filterbank architecture. This implementation demonstrates the efficiency and ease of use of 2DLNS CPU in real applications.
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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 | 0.001 | 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 | 0.002 | 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