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To discuss the convergence of the subgradient extragradient method, we make the following assumptions.
In the LPG-PCA method, we make the size of the variable block and training block 2 and 20, respectively.
In our current sparse method, we make no assumption of the surface reflectance property and treat all non-Lambertian effects (specularity and shadow) equally.
However, in our method, we make use of the fact that there is only one CFO and only one DOA for each user, and these two parameters are directly estimated by the designed rank reduction approach.
To demonstrate the effectiveness of AN method, we make many experiments on a series of synthetic data with different SNR from −1 dB to −12 dB and compare it with previously published Akaike information criterion (AIC) and short/long time average ratio (STA/LTA) methods.
To foster widespread adoption of this method we make it available as an open-source software-package – epicode at https://github.com/mcieslik-mctp/epicode.
Similar(54)
In order to improve the efficiency of the proposed method, we made a special effort to demonstrate the analytical methodology.
In order to verify the effectiveness of proposed method, we made an experiment to compare the proposed method with references [5, 6] by the CMOS.
For the L-ME method, we made the following assumptions: First, the position of accent commands will be close to the location of syllable with lexical stress.
To demonstrate the reliability of our proposed method, we made comparison with the Matlab b v p 4 c routine technique, and an excellent agreement was observed.
Method: We made a design of limited cone-beam X-ray CT so that it could be most effective for dentistry use.
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