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Since the accurate reconstruction quality can only be obtained after de-quantization, the proposed quality estimation reduces the computational complexity of de-quantization process for each candidate modes.
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Early termination and refinement for candidate modes are considered to trade-off computational efficiency and accuracy.
The most significant bottleneck in our algorithm is the computation of a matrix rank for every candidate mode.
The distribution of the histogram leaves only a small number of the candidate modes for the RMD and the RDO processes.
The numerical value of criticality index for each candidate is derived based on the information available from failure mode and effects analysis (FMEA) document or warranty data from a prior system.
In order to prevent the exponential growth in the number of candidate modes, we randomly select a sample of the new candidate modes at each step.
"Speeches for each candidate just halfway in".
For each candidate rotation angle, all candidate scaling factors are required to search.
WeNB variable stores the weight for each candidate eNB.
H and Z path are obtained for each candidate TS.
For each candidate a confidence is computed as follows: (8).
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