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The corresponding weight matrices are estimated, and utilized to estimate the underlying sources.
The uniform ultimate boundedness of the visual servoing error and the neural network weight matrices are proved by Lyapunov theory.
Both weight matrices are row normalised, in order to get a value of one as a row sum.
Hence, it supports Hypothesis 2. Nevertheless, the other spatial weight matrices are significantly negative to housing prices in affected countries, which is converse to traditional wisdom.
The relay weight matrices are concurrently designed to optimize the mean square error (MSE) criterion at the destination, assuming each relay node is subject to a power constraint.
Moreover, the results are also extended to the pure competition networks where all the elements in the weight matrices are either zeros or negative.
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P-values and position weight matrices were calculated using the Wilcoxon-Mann–Whitney test.
Thirteen weight matrices were reported for φ = 0.9 (one for η = 3% and thirteen for η = 4 or 5%) in Table 1.
Using these polygons, adjacency-based weight matrices were constructed.
Binding sites weight matrices were also generated by hidden Markov training using MAMOT software [ 59].
Position weight matrices were generated using Gibbs Motif Sampler, for every site included in the program.
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