The difference between two coefficients is not significant, so we consider that the linear approximation is precise enough to estimate the convergence time of the FAPH algorithm for the number of spectral opportunities to be evaluated.
However, our aim was to provide an approximation (not precise dating) for times of lineage splitting.
Using tools from the theory of operator ideals and s-numbers, we develop a general approach to transfer estimates for L2-approximation of Sobolev functions into estimates for L∞-approximation, with precise control of all involved constants.
This method, in contrast to the traditional finite-difference approximation, gives highly precise numerical result, which approaches the full computer precision.
A number is Turing-computable if there exists a Turing machine which starting from a blank tape computes an arbitrarily precise approximation to that number.
It is obvious that the quadratic approximation is not precise enough to focus the image in CTSSAR and the time domain BP algorithm seems to be trusted to handle this task perfectly.
As can be seen in Figure 2a, a small number of terms is required to obtain a precise approximation when the channel is characterized by severe fading (κ=0.5,μ=1.5) – in this case, a total number of W2=16 terms is used.
For a more precise approximation of different local differences, the Reininghaus District was split into 17 groups of buildings as they will be described in the case study description in chapter 3.
This observation encourages one to limit computations of the double sum in Equation 14 only to the neighborhood N i) of node i and yet get a potentially close approximation of the precise value of partial derivatives.
