Sentence examples for many iterations in from inspiring English sources

The classification of epileptic seizures and epilepsy is a controversial and dynamic topic that has undergone many iterations in human medicine.

The Quantum fund, which has existed in many iterations in its more than 40-year history, has returned about 20 percent a year on average, according to a person briefed on the matter.

Thus, a capacity model at steady-state conditions was then used for performing many iterations; in each iteration, the values of the model parameters were randomly drawn from the corresponding probability distributions.

Indeed, for the NLMS algorithm there are many iterations in which (|tilde {mathbf {w}} k+1)|^{2}>|tilde {mathbf {w}} k)|^{2}), even when using a small step-size μ.

The results depicted in Fig. 3 illustrate that, for the general CV, there are many iterations in which g 1 k)>g 2(k) (about 293 out of 1000 iterations).

Even when a low value of μ is applied we still observe many iterations in which (|tilde {mathbf {w}} k+1)|^{2} > |tilde {mathbf {w}} k)|^{2}) (425 out of 1000 iterations).

The idea would have many iterations, but in essence, it was based on citizenship independent of faith, as Syrians, Egyptians, Arabs or others.

This is particularly concerning as there are so many iterations involved in developing machine-learning tools and there is no universal benchmark of good practice for implementing and recording them all.

In the iterative SIRT method, choosing a certain number of iterations can be viewed as a type of regularization: in general, using few iterations will result in images with less noise, but less high-frequency details as well, while using many iterations results in images with more details but more noise as well.

The disadvantage of iterative approaches is that they generally require many iterations as shown in the study of [7] where max-SINR [6] is extended for the cellular networks.

Furthermore, PSO is sometimes criticized because many iterations are performed in comparison to gradient-based optimization algorithms.