Sentence examples for multiple iterative from inspiring English sources

In order to calibrate the channel model, the algorithm requires multiple iterative computations, so large amount of energy is consumed.

However, both consensus or flooding-based solutions are very costly in terms of bandwidth requirements as they require multiple iterative inter-node communication between two consecutive sensor measurements.

Both EZW and SPIHT need the coefficient tree construction to search for significant coefficients through a multiple iterative process at each bitplane, which involves high computational complexity.

Through this model, the influence of the wheel profile, primary suspension stiffness, track gage, and rail cant on the wear of the wheel profile were studied through multiple iterative calculations.

An alternative to circumvent the high communication cost of consensus algorithms is to use diffusion algorithms[16] which, contrary to the former, do not require multiple iterative inter-node communication between consecutive measurements.

Through this model, the influence of the wheel profile, primary suspension stiffness, track gage, and rail cant on the wear of wheel profile were studied through multiple iterative calculations.

It is common in wavelet image analysis to use multiple algorithms, iterative algorithms and other combinations of image processing techniques.

"Large Agile teams manage dependencies through multiple and iterative synchronization points, but they also work to remove them through better design process like Lean's set-based and concurrent engineering approaches," Martens says.

Table  1 provides an overview of the multiple and iterative methods used in our instrument development process, and the sample size used for each step.

Iterative multiple linear regression was performed using the stepAIC subroutine from R, in both the forward and reverse directions over 1,000 steps.

This model is often simulated by computationally intensive methods like finite elements and discontinuous Galerkin, while some recent applications require more efficient approaches (e.g. for real-time clinical decision support, phenomena occurring over multiple cardiac cycles, iterative solutions to optimization/inverse problems, and uncertainty quantification).