A Pipeline VLSI Architecture for Fast Computation of the 2-D Discrete Wavelet Transform
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, a scheme for the design of a high-speed pipeline VLSI architecture for the computation of the 2-D discrete wavelet transform (DWT) is proposed. The main focus in the development of the architecture is on providing a high operating frequency and a small number of clock cycles along with an efficient hardware utilization by maximizing the inter-stage and intra-stage computational parallelism for the pipeline. The inter-stage parallelism is enhanced by optimally mapping the computational task of multi decomposition levels to the stages of the pipeline and synchronizing their operations. The intra-stage parallelism is enhanced by dividing the 2-D filtering operation into four subtasks that can be performed independently in parallel and minimizing the delay of the critical path of bit-wise adder networks for performing the filtering operation. To validate the proposed scheme, a circuit is designed, simulated, and implemented in FPGA for the 2-D DWT computation. The results of the implementation show that the circuit is capable of operating with a maximum clock frequency of 134 MHz and processing 1022 frames of size 512 × 512 per second with this operating frequency. It is shown that the performance in terms of the processing speed of the architecture designed based on the proposed scheme is superior to those of the architectures designed using other existing schemes, and it has similar or lower hardware consumption.
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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 | 0.000 | 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