Sentence examples for maximizing the array from inspiring English sources
In this work we propose three different methods to compute optimized filter coefficients with the purpose of maximizing the array gain and minimizing distortions, and with the objective that these filter coefficients are valid for all users.
On the other hand, the potential super-directive properties of dense arrays are long since known, and super-directivity is defined mathematically as the solution to an optimization problem, namely, the search of the weighing window maximizing the array directivity for a fixed array response in the steering direction [12, Sect. 9.2.1 and overview notes in Sect. 9.1].
Therefore, by regarding the steering vector ( {mathbf{a}}_{a,0}left {theta}_0^{prime}right) ) as a variable, the actual steering vector a a,0(θ 0) may have possibility to be estimated by maximizing the array output power under the assumption of great capability in anti-interference performance.
It is known that solving the optimum weighting vector for the maximum DF is equivalent to maximizing the array gain G in an isotropic noise field [2, 11], i.e., mathbf{w}_{text{opt}} = arg mathop{max}_{mathbf{w}} frac{left| mathbf{w}^{mathrm{H}} mathbf{a}left phi_{0}, theta_{0}right) right|^{2}}{mathbf{w}^{mathrm{H}} pmb{rho}_{mathrm{n}} mathbf{w}}, (4).
We optimized the two thresholds for each set of SMD arrays, maximizing the area under a curve plotting the number of genes incorporated in the inferred linkages versus cumulative log likelihood score of the linkages (Table 2).
We optimized the choice of these two parameters for each set of array experiments by maximizing the area under a recall-precision curve (Table 2).
The optimization method is based on maximizing the utilization of the array output energy, and, at the same time, minimizing the electricity power sold to grid.
Herein, we prove that waveform design based on the criteria of maximizing the output SINR of array signal processing can be formulated as optimization problem in (8).
Thus, in our laboratory, all cDNA arrays are imaged for quality control prior to hybridization, maximizing the use of quality arrays for subsequent experimental procedures.
Finally, for each gene one ps was selected for further analysis by the criterion of maximizing the expression variation across arrays and thereby the most informative ps was chosen for each gene.
The distribution of data points for each position is then evaluated for a bimodal distribution while maximizing the number of individual arrays under each peak.
