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Using the algorithm of Little et al. (2007), we generated 1/f α noises with nine intended alpha values of 0.0 to 2.0 in 0.25-step intervals, and in sample sizes (vector lengths) of 512, 768, 1024, 1536, 2048, and 3072.
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In the classical problem, the bin size vector is given and the sequence can be partitioned arbitrarily.
We study a variation where the vectors have to be packed in the order in which they arrive, and the bin size vector can be chosen once in the beginning.
Population-size changes were modelled by the recurrence equation x(j+1)=Bjx j), where j was the 15-day phase, x an age-class population size vector and B a fecundity-, mortality-, offtand- and intake-rate matrix.
The data symbol vector is a size vector.
where is a size vector and is obtained by eliminating terms from.
In this algorithm, the step-size vector with different values for each filter coefficient was used.
Accordingly, optimal step-size vector is obtained by minimizing the mean-square deviation (MSD).
Recent research shows that representing input in a fixed size vector does not provide the best results for certain tasks, like translation.
where c is a N c size vector that represents the constraints to be kept into account in state estimation.
The frequency spectrum represents the large size of time-domain data in a small size vector and removes the repetition of the data features.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com