Sentence examples for project matrix from inspiring English sources

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From this result we can see that most elements of this project matrix are near to zero, which accords with the sparse constraint of NTPCA. Figure 4(b) gives several samples for coefficients of feature vector after projection, which also prove the sparse characteristic of feature.

For our analysis of individual fitness as determined from our age-specific project matrices, we followed the advice of Caswell (2001) and used a bootstrap method to estimate 95% confidence intervals (Kalisz and McPeek 1992) as implemented in Matlab (The Mathworks).

And the projected matrix is reconstructed based on weighted subspace basis: R i, p = f ̂ i, l × W l, p + 1 MN ∑ i = 1 MN f i, p (12).

The projected matrix A ̄ i is obtained by minimizing the Frobenius norm of A ̄ i - A ~ i (according to [18]) subjecting to (18), which can be formulated as the following optimization problem: min A ̄ i tr ( A ̄ i - A ~ i ) ( A ̄ i - A ~ i ) H (20) s.t.

We also noted that Yang et al.'s method can be adaptive to the alteration of sensor configuration by constructing a global projecting matrix, thus it has advantages over Huynh's as well as our approach in dealing the problems if one or more sensor nodes (or sensor) failures.

Empirical tests suggest that the most effective smoothers have to be of Krylov type with subgraph preconditioners, while the projectors, which define the coarser-grid operators, have to be designed for maintaining as much as possible the graph structure of the projected matrix at the inner levels.

The vectors of the projected matrices (mathbf {H}_{kk}^{bot }), ∀k≠k ∗, are in the null space of all previously selected streams.

Finally, by approximating the projected matrices with the Chebyshev interpolation technique, RSRR is further extended to solve NEPs in the boundary element method, which is typically difficult due to the densely populated matrices and high computational costs.

As we consider the orthographic camera model, the camera motion matrix R t in Eq. (2) is obtained by projecting a 3D rotation matrix to 2D with an orthographic projection matrix begin{array}{*{20}l} boldsymbol{Pi} = left[ begin{array}{lll} 1 & 0 & 0 0 & 1 & 0 end{array} right], end{array} (9).

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