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We present several numerical results to show the performance of the error estimator.
Then corresponding graphs show average performance of the error correcting codes, BER (bit error rate) against the attack type for the different image sizes.
The performance of the error compensation will be degraded in such area, while the accuracy is still better than the result without any compensation.
However, if the simple MKL is used for estimating the parameters of the linear combination of kernels, successful performance of the error degree estimation is not possible.
The interleaver in the SCCC encoder has a main role in the performance of the error correcting code: it introduces the randomness necessary for iterative decoding.
The purpose of this article is to be able to evaluate the performance of the error correcting codes with reference to each attack type.
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The performance of the error-entropy minimization is compared with the mean-square-error minimization in the simulation results.
Although this is not the focus of this work, we may use the relative achievements to enhance the performance of the error-amending model in future.
In most of the standards, such as long-term evolution (LTE) standard [27], the encoding is performed in a systematic form in order to facilitate the decoding process without degrading performances of the error correction.
To evaluate the performance of the proposed error concealment method, first only errors in WZ frames are simulated.
This provide some interesting insights on the small sample performance of the prediction error method.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com