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For example, this could allow us to discriminate between the error vectors occurring along the animal path to the error vectors occurring laterally to the animal path.
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For the equilibrium synchronization case, it is shown that there is a close relationship between the L2 norm of the error vector e and the H2 norm of the transfer function G of the linearized network about the equilibrium point.
From Definition 1, we obtain the error vector between two drive systems (5), (6), and one response system (7) as follows: e(t)=z-M_{1}x-M_{2}y. (9) Calculating the derivative of the error vector (9) and with the designed controller (8), we conclude that dot{e}(t - C-K e(t - C-K e
Since the error vector can be calculated by computing the error between reprojected position from 3D point and the measured 2D point, δP is the only unknown in the equation.
This difference is called the error vector.
where e is the error vector.
Z ∈ Rt × 1 is the error vector.
Update of the error vector: e = x - F g k.
Let us define the error vector as (4).
We also assume that the error vector (e_{i1}geq{e_{i2}}geqcdotsgeq{e_{in}}).
{begin{array}{rcl}{displaystyle {E}^u}& =& {displaystyle {sum}_{i=1}^Lleft(begin{array}{ccc}{displaystyle {X}_i^u}& -& {displaystyle {C}_i^v}end{array}right)}end{array}}^2 (3)where Ε u is the error or distortion between the error code vector Xu and the error code word C v. Fig. 7 Codebook generation.
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CEO of Professional Science Editing for Scientists @ prosciediting.com