Under the previous assumption of perfect knowledge of the channel coefficient and the noise variance, the problem is a convex optimization problem with the parameter P RD i and P SR i.
The highly non-linear differential equations with variable coefficients governing the problem are solved numerically using a Runge Kutta method.
However, in practice, we may be faced with some situations where the coefficients in the problem are uncertain.
Therefore, we do not dispute the statement by Okoniewski and Miller that MT can alter the estimates of correlation coefficients constructed from microarray data, albeit the problem is definitely not as extreme as presented by these authors (see Section 2.1 for details).
However, in Hochbaum et al, 20 it is also mentioned that finding solution that maximizes Kendall tau rank correlation coefficient is a difficult task because the problem is (non-deterministic polynomial-time) (NP -hard.
The novelty of this paper is that the necessity condition and local uniqueness of optimal control to the problem are obtained with viscous coefficient (varepsilon>0).
The regions are represented using Fourier-cosine coefficients and the optimization problem is solved numerically using a quasi-Newton method.
Moreover, for all the Fourier numbers considered, the numerical solution is stable and oscillation-free when the optimal coefficient of the model problem is used.
What's the Green's function when the spike is moved along to a point t? Just, because this constant-coefficient, translation-invariant, LTI problem is shift invariant, the answer, when the spike is moved along, is just the answer G moved along.
In this case, it is enough to observe that an optimal solution exists in which variable ρ takes a value from a set of at most n + 1 candidates; once ρ is fixed, the resulting problem is a nominal problem in which some coefficients are changed.
