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For predictor variables, thin-plate splines were used, initiated with a dimensional basis of two, thus ensuring simple response curves.
For that purpose, we decompose the precoding matrix in terms of the S dimensional basis U u and a basis (mathbf {U}_{u}^{perp }) of its N t −S dimensional orthogonal complement: begin{array}{*{20}l} mathbf{F}_{j} &= mathbf{U}_{u} mathbf{F}_{j}^{parallel} + mathbf{U}_{u}^{perp} mathbf{F}_{j}^{perp}, end{array} (39).
By representing Φ0 in a finite dimensional basis the problem is discretized.
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The approach uses a low-dimensional basis function set that contains both global and local, goal-oriented basis functions.
The high-temperature drying of a softwood board with relatively high permeability was modelled on a one-dimensional basis.
Now, the one-dimensional basis is extracted from the existing bivariate functions to achieve a one-dimensional expansion for x[ n] as in (3).
CS approaches are particularly suited for K-sparse signals, i.e., signals that can be represented by significant K coefficients over an N-dimensional basis.
The basis patches along the top and left sides are the same as the one-dimensional basis elements, except they have been copied to fill the second dimension.
If successful, such an approach will be able to improve the ability to observe materials dynamics in any TEM imaging system. 1 An N-dimensional basis can be formed by taking the Kronecker product of N copies of the 1-dimensional basis. 2 The sensing scheme must satisfy the restricted isometry property or be incoherent with the measurement basis [50].
The general description of these three-dimensional basis functions, which can be used for a rather wide spectrum of problems, is presented.
The Bethe Ansatz method is employed to show that our discrete Laplacian and its commuting integrals are diagonalized by a finite-dimensional basis of periodic Macdonald spherical functions.
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