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The paper presents a reversible audio data hiding scheme by using noncausal prediction with alterable order.
This paper presents a reversible data hiding scheme for digital audio by using noncausal prediction of alterable orders.
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The other, more important, advantage of the approach is that the current pixel can be estimated in a single pass by using noncausal predictive way to improve prediction performance 2. From the expression (y_{w}=hat {y}+2times e + w) in Eq. (2), we find that in order to recover the marked pixel y w, not exact of an integer (hat {y}) is needed, but of the sum of (hat {y}+2times e).
It does this by using price prediction algorithms that take into account billions of observed price movements and over 40 distinct factors to offer comprehensive predictions.
According to the results of [15] the overall prediction accuracy increases by using different prediction algorithms for different workloads.
Potential bias in the predictions was assessed by using median percentage prediction error (MPPE).
2In the literature [15,26], noncausal predictive methods have been used for the IPE by using multi-passes prediction for multi-layers embedding.
This can be done by raster scanning the pixels in the first two rows and predicting the 2×C pixels by using the noncausal predictor in the case of p=1, described in Section 3.3.
This can partially be compensated by using channel predictions.
Amino acid VP1 secondary structure predictions were made by using PSIPRED secondary structural prediction software (25 ).
d Noncausal prediction using bilinear interpolation with two past pixels and two future pixels.
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