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Existing techniques use various coding schemes to provide information redundancy needed for error detection and correction.
Based on the extensive performed simulations, it is concluded that in the CED method, if bits are needed for detecting an error after it has occurred, bits are needed for error detection in our proposed method.
Furthermore, side information (e.g., parity bits) is needed for error correction and this may lead to information leakage (i.e., some attacks like error correcting code statistics, and non-randomness attacks) [13].
Multiscale computational modeling of motor learning based on plasticity mechanisms within populations of cells has shown two conditions where motor learning fails: (1) lack of the sensory information (or attention to the sensory information) needed for error correction; (2) large performance errors so that incorrect movements are being practiced [49].
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It is also possible that Srs2 could facilitate the generation of substrates needed for the error-prone or error free sub-pathways of PRR [45,54].
This indicates that, given the parameters for existing state-of-the-art transmon/cavity systems, multi-qubit measurements of quality near that required for fault-tolerant error correction could be performed, but that further improvements in control design and/or hardware parameters would be needed for threshold error rates to be attained.
An absolute scale that combines consistent clinical information with statistical relevance is needed for wavefront error mapping.
As a result, a large portion of the computations needed for propagating error covariances and updating state estimates can be neglected.
The following lemmas are needed for our error analysis.
Then, the tool-work relative vibration errors, i.e., the vibration errors needed for the dynamic error modeling [21], which can be obtained by the machine and cutting dynamics simulation.
The findings demonstrate that novel manufacturing process, tooling, and algorithms are needed for achieving error-free manufacturing of fractals.
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