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By solving the RCB, the positioning information in three dimensions is obtained by utilizing a linear equation.
This issue is formulated in a discrete-time framework by utilizing a linear iteration scheme, where each node repeatedly updates its value as a weighted linear combination of its own value and those of its neighbors.
Statistical testing of possible restructuring and suddenness interaction effects on reaction time, i.e. time to generate solution, was performed by utilizing a linear mixed-effects model [function lme from package nlme in R] which was estimated by Restricted (or Residual) Maximum Likelihood [88], [89], [90], [91].
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By constructing and utilizing a linear combination algorithm (Supplementary Figure 1), similar to the one used for CH3 and CH2 above, pure signals of proteins labeled by group I D-AAs and by group II D-AAs can be successfully separated and quantitatively visualized.
The column was equilibrated in 85% A/15% B prior to the injection of the sample, and upon injection this composition was then changed to 60%A/40%% B over 30 min utilizing a linear gradient followed by changing to 50%A/50%% B over the next 10 min, and then, the concentration was returned to 85%A/15%% B over the final 10 min.
Required pressing force is measured utilizing a linear servo driven press and the data is plotted into into Matlab as polynomial surface function and is then utilized in multi-dynamics program Adams by Simulink-interface.
In addition, it exploits the available bandwidth more efficiently by utilizing a single preamble of linear-frequency-modulation (LFM) to detect the start of the packet.
Sufficient conditions for the solvability of the two problems are obtained by utilizing a Lyapunov functional together with the linear matrix inequality (LMI) approach.
This paper proposes a new technique for improving the performance of linear prediction analysis by utilizing a refined version of the autocorrelation function.
For each case, by utilizing a convex combination technique, the resulting synchronization criterion is formulated as the feasibility problem of a set of linear matrix inequalities (LMIs).
In this paper, by utilizing a different technique, we prove some coupled fixed point theorems in a partially ordered Φ-orbitally complete normed linear space.
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