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We first present shortly the classic algorithm for selecting the pertinent modes of a signal.
The procedure combines a genetic algorithm for selecting the best inputs with an ANN ensemble method.
In this section, we first show the SSIM-based algorithm for selecting the optimal known patches in Section 3.1.
Zeng et al. applied a hybrid algorithm for selecting the individual HRTFs based on the similarity of anthropometric structures [10].
From the results in Figures 3 d) and 3 e), the effectiveness of the algorithm for selecting the optimal known patches in Section 3.1 can be confirmed.
To calculate and validate a new web-based algorithm for selecting the back optic zone radius (BOZR) of spherical gas permeable (GP) lens in keratoconus eyes.
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In the next section, we describe the iterative reconstruction method and two algorithms for selecting the locally best smoothing parameter, h, for each HDR pixel estimate, z j, individually.
We chose two measures to evaluate the performance of algorithms for selecting the best individuals.
We compared the performance of the six regression algorithms for selecting the best 15% of the individuals (using the same 50 random partitions).
In this study, we compared the performance of six regression and three classification algorithms for selecting the best individuals in maize and wheat data sets using high-throughput molecular marker information.
A sensor selection algorithm (SSA) for selecting the best set of sensors is presented in this paper.
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