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In this case, the global optimum can be found.
Thus, finding a global optimum can be difficult.
Finally, a good local optimum can be obtained after convergence.
For CGPs, only a local optimum can be obtained efficiently.
This optimum can be different for different applications.
However, for specific network instances, global optimum can be achieved using numerical solvers.
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The optimum ratios can be achieved by adjusting the feedstock carbon and nitrogen contents.
It is shown that the optimum threshold can be extracted from the noisy coefficients themselves.
Different facets are deciphered so that optimum results can be attained.
and, therefore, the optimum constellation can be approximated with the solution of the following problem: (14).
6, an optimum span can be considered for each method and noise level.
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