Using the theory of chemical reaction networks (CRNs) and previous results on dynamical equivalence, a complex balanced or weakly reversible zero deficiency closed loop realization is achieved by computing the gain matrix of a polynomial feedback using optimization.
CO2 interannual variability was calculated by (1) detrending the observed time series at each site with a third-order polynomial, (2) computing a mean annual cycle from the detrended time series, (3) removing the mean annual cycle from the original time series, and (4) fitting a third-order polynomial to the time series obtained from step (3) [ Keppel-Aleks et al., 2013].
The residuals of all-day annual and monthly means are computed by removing a polynomial fit from their best fitting curves.
The chromatic number of the graphs is computed using a polynomial complexity algorithm.
By computing the recurrence relation, the q-polynomials are represented as h k ( t, s ) = ∏ ν = 0 k − 1 t − s q ν ∑ j = 0 ν q j. on q N ¯ [1].
The features in (hat {mathbf {P}}), interpreted as elements of a finite field F where |F|=ρ, are bound to the secret polynomial κ by computing (V(X)=kappa (X)+prod _{vin hat {mathbf {P}}} X-v)), such that the pair (V(X),SHA builds our final record.
In the selected time interval, we detrend the time series ((H_mathrm{External})) by computing the average long-term trend using a seventh-order polynomial fit p t).
This novel approach is devoted to presenting an algorithm that permits to solve the problem of blind image deconvolution by computing greatest common divisors (GCD) of several polynomials.
A polynomial regression analysis allows us to estimate the average network sensitivity S = [dM x)/dx]x = 0 by computing the slope at the origin of the best-fit polynomial with a degree equal to the maximum number of regulators per gene in each case (this is the polynomial predicted by the mean-field theory).
Although from Lemma 1.1 we can verify the positive definiteness of an even-order symmetric tensor (mathcal{A}) (the positive definiteness of the mth-degree homogeneous polynomial (f(x))) by computing the H-eigenvalues of (mathcal{A}).
