Sentence examples for restrict the parameters from inspiring English sources

A novel aspect is that we restrict the parameters in the original problem to only appear in affine functions, which lets us map the parameters to problem data without performing any floating point operations.

For half an hour in the first half they were either making tackles close to the breakdown, as Ireland tried to inflict some physical punishment and restrict the parameters of the contest, or they were getting their own wires crossed in midfield trying to get in behind the Irish defence.

Accordingly, it is reasonable to restrict the parameters that the attackers will change to transmitted power and occupied spectrum bandwidth.

Regarding the weather conditions and in order to restrict the parameters that affect the riding behavior of the participants, both riders instructed to cease the measurements when the pavement was even slightly wet.

If we restrict the parameters a and b to discrete values as (a=a_{0}^{-j}), (b=mb_{0}a_{0}^{-j}), where (a_{0}>1), (b_{0}>0), and j, m are positive integers, we have the following family of discrete wavelets: psi_{j,m}(t)=|a_{0}|^{j/2}psibigl(a_{0}^{j}t-mb_{0} bigr), which form a wavelet basis for (L^{2}(mathbb {R})).

So in order to improve the simulations, that is in order to remove this growth trend in the simulated variances in Figure 5, it would be really worthwhile to restrict the parameters estimates of the model to those belonging to this subset.

Previous approaches to the Six Cities dataset overly restrict the parameter space but, by considering the correct invariance, the maximum likelihood is quite naturally improved when treating the full unrestricted model.

In this case, we restrict the parameter ranges (0le alpha <0.25) and (0.6<q<1) based on the study [33].

To restrict the parameter search space, an optimization scheme is designed as follows: 1. Find optimal N and R for LBP using a tenfold cross-validated 1-NN classifier.   2.

It has been shown that it is meaningless to search for the ML of σ 2 in the domain (0,+∞) P. A possible solution is to restrict the parameter space by imposing a priori lower bounds of the form [17] begin{array}rcl@ 0<delta_{p}^2 leq hat{sigma}_{p}^2 end{array} (12).

The Bayesian hierarchical implementation, however, borrows strength across participants through group-level structures, uses prior knowledge about plausible parameter values to restrict the parameter space and produces posterior distributions to indicate the uncertainty about the parameters at hand.