This indicates that if we are able to choose interpolation points such that (Lambda_{n} ) is small, then we can find the Lagrange interpolant that is less sensitive to errors in the function values.
Inequality (4.14) corresponds to the absolute error in approximating the function by for the th iteration.
Inequality (4.11) corresponds to the relative error in approximating the function by for the th iteration.
Results show that the proposed linearizations and approximations produce accurate solutions when compared with a nonlinear three-phase OPF formulation, with an error in the objective function near to 2% and a maximum error in the voltage near to 1%.
Because it is based on the Central Limit Theorem of probability, the sampling-the-mean algorithm also gives estimates of the error in the partition function, ensemble averages, and density of states.
However, from Equation 3, the main impact of carrier tracking is the frequency error in the 'sinc' function, which only serves to attenuate the power passing through the tracking loop.
The index n in is the power or weight of the considered error in the energy function of the segmentation problem, and V kl is the output of the kl th neuron.
We have shown, empirically, that considering an integer power equal to six, of the error in the energy function of the problem, helped SCHNN to converge twice as fast as the same optimal solution obtained with the mean-square error algorithm.
Compared to more accurate simulations, these guidelines result in an average approximation error in the transfer functions of 1.3 dB in the third octave band SPLs while considerably reducing the evaluation time.
As we examine larger proteins, their potential energy surfaces should become increasingly more distorted due to increased random error in the energy functions, which can have unpredictable effects on the free energy landscape.
