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This is a first degree approximation to Michaelis-Menten type of kinetics like the formulation used for peptide-dependent T-cell activation.
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Second, one may generate low degree approximations (e.g. using spline functions) for the Hermite boundary data.
By using low degree approximations (e.g. splines) for the Hermite boundary data we obtain (spline) surface patches of low degree.
The RSM develops an adequate functional relationship between input variables and interested responses by low-degree approximation of the polynomial models such as the second degree model (Eq. 2) [32].
However, these observations are good in only first-degree approximation since molecular profiling of tissue whole mass cannot capture the incredible heterogeneity of cancer populations [ 17].
Table 10 Setting of parameters of the adaptive MEgPC approach for the biofilm model Degree of approximation p ˆ 5 Order of approximation p 3 Tolerance (time) TOL 5⋅10−6 Tolerance (elements) ε × Refinement threshold ρ 1 × Coarsening threshold ρ 2 ×.
Now, let us give a lower estimate for the exact degree in approximation by W n, q α, β.
They do not address the question of whether individual functions can be approximated better than what the degree of approximation theorem predicts, based on the a priori information known about the target function.
One of the basic problems in the theory of approximations of functions and the theory of Fourier series is to examine the degree of approximation in given function spaces by certain methods.
In this theorem, we propose a polynomial time algorithm for computing an approximate solution to the Walrasian equilibrium inequalities, where explicit bounds on the degree of approximation are determined by observable market data.
The degree of approximation can be controlled at runtime.
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