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The proposed method is generalization of Kumar's approach.
The second method is Generalization: In this method, individual values of attributes are replaced with a broader category.
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These methods are generalizations of the traditional Capon and MUSIC methods to the 3D configuration.
All the above mentioned ADMM-type methods are generalizations of the classical ADMM, because they all reduce to the iterative scheme (4) by choosing some special parameters.
The methods are generalizations of classical optical flow techniques, including a production term (modelling formation, growth or depletion of clouds) in the model to be fit to the data.
The presented methods are generalizations of the numerical scheme introduced in [2], where the solid immersed in the fluid is rigid and has the same density with the fluid.
As pointed out in [9], one problem the model-based methods face is generalization to different input signal-to-noise ratio (SNR) levels (note here that we consider interfering speech as noise).
The method of finding these solutions is generalization of the method developed in our earlier work (2005b), where the analytical solution for the groove of the simplest shape, was obtained.
This method is a generalization of the hyperparameter method constructed by Lahav et al.
The proposed method is a generalization of the convex approximation method.
The method is a generalization of a method previously proposed for vertical boreholes.
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Justyna Jupowicz-Kozak
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