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The current algorithm presents errors in words containing vocalic sequences in the final position.
Nevertheless, the average RMSE obtained for all subjects shows a better performance of our method with respect to [ 39], an optimization-based approach which presents errors around 3.5 degrees.
BLAST2 presents errors when one sequence under comparison contains mononucleotide repeats with runs greater than six nucleotides; n is indicated in place of each repeating nucleotide at those positions and considered "non-matching" in similarity calculations.
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Figure 6 presents error in terms of cumulative distribution function (CDF).
The last section presents error estimates via wavelet dual least squares method approximation.
The neural network presented a maximum error value lower than 30%, while existing formulas presented errors greater than 40%.
These three methods present errors of less than 5%, involve low to medium cost, and the maintenance operations are simple.
In addition, the prediction equations only presented errors below 7% for the evaluated variables, with R2 values above 0.85.
The results on allele size were always repeatable while the sequences presented errors due to slippage.
In this paper, we present error concealment approaches for two different four-description MDC architectures.
The presented error bars correspond to standard errors of 4, 8, 10, 11, 12 and 21 (Table 4).
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