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The inverse problems are formulated into parameter-identification problems, in which a set of parameters corresponding to the characteristics can be found by minimizing error functions formulated using the measured dynamic behaviors of structures and that computed using forward solvers based on projected candidates of parameters.
MV for the block can be found by minimizing (6), subject to the constraint on RB.
The (hat {alpha }) and (hat {beta }) estimates can then be found by minimizing Eq. (2).
The optimal quantizer and the predictor can be found by minimizing the MSE (sigma _{epsilon }^{2}=E left {epsilon _{n}^{2} right }).
The missing calibration parameters m, q and γ can now be found by minimizing the error e with a least square method.
Thus, an optimum parameter q can be found by minimizing the CE between the two distributions f(ω;q) and f.
Similar(42)
In order to achieve the minimal variation in responses, the optimal factor settings were found by minimizing the propagation of error (POE).
The complete relaxed state is found by minimizing the total energy, using a variational method.
Here, the OLH is found by minimizing the Audze Eglais potential energy of the points using a permutation genetic algorithm.
Then the optimal off-design AUVs in tactical subspaces were found by minimizing the difference between the locally optimized objective function and sub-optimal objective function.
These coefficients are found by minimizing the error between these fractional-order transfer functions and the second-order transfer function using numerical least squares optimization.
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CEO of Professional Science Editing for Scientists @ prosciediting.com