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Secondly, by using local region growing and interactive level set segmentation methods, we can get the actual boundary of each axon which can provide us valuable quantitative information such as the length, radius for axon function and connectivity analysis.
As the true evolutionary relationships in this case are unknown, we used orthologs inferred by the GETHOGs and Inparanoid algorithms as reference: by considering the intersection and union sets of orthologs inferred by the two methods, we can get approximate lower and upper bound estimates for the performance of BBH.
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Using the same method, we can get inequality (3.4).
Essentially by the same method, we can get the multiple existence results for BVP (1.1), (5.1).
By the same method we can get that (L: Krightarrow K) is a completely continuous operator.
By using this method, we can get 19 pieces of emitters on each 3-in.
By using this encoding method, we can get a decimal number for each pixel corresponding to its directional pattern.
By utilizing the extrapolation method, we can get numerical solutions with higher convergence order from (3.3), (3.16), and (3.23), respectively.
Using this method, we can get a higher degree of shift invariance and a better directional selectivity[9].
By a similar method, we can get the following inequality which does not contain the weight so we omit the proof.
According to the above method, we can get the optimal rotation angles for proposed scheme based on various parameters without predetermined operating SNR.
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