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The principles of the shrinkage estimators which estimate the frame coefficients from the observed coefficients have been discussed in different frameworks such as Bayesian and variational regularization [20, 21].
The effectiveness of this method is clear from experimental results on frame rate estimation in the presence of packet loss (Section 4.1.2), since timeIncrement is used to estimate the frame rate.
The first equation allows to estimate the frame's yield displacement based only on its effective height.
The second equation permits to estimate the frame's strength based on the effective weight, effective height and fundamental period squared.
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With these assumptions, we could estimate the frame-shift mutation rate of individual mononucleotide repeats, and we could sum up the estimated frame-shift mutation rates over all repeats in a genome to get an estimate of the genome-wide frame-shift mutation rate.
We derive a mathematical model for estimating the frame non-delivery probability and the traffic load from overhead, and demonstrate the general correctness of the model by simulation.
In [26], a set of motion filters are employed for estimating the frame dominant motion in an attempt to detect semantic events in various sports videos.
First, we estimated the frame-shift mutation rate in mononucleotide repeats in coding regions of the M. tuberculosis genome.
Then, we estimated the frame-shift mutation rate that would be expected if codons were used at random, irrespective of the local context.
To do so, we analyzed the randomized genomes, where codons were used in a context-independent manner, and estimated the frame-shift mutation in mononucleotide repeats in the same way as we did for the actual genome of M. tuberculosis.
The two interpolated frames between frames 3 and 5 will be merged into a new reconstructed one while a new frame is interpolated between frames 5 and 7 to estimate the lost frame 6.
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