Sentence examples for model for noise from inspiring English sources

A theoretical thermal model for noise in multi-pixel devices reasonably explains the experimental data.

The paper discusses novel examples of the associative memories using the cerebellum model for noise modeling.

In order to accurately predict the noise, all analyses are carried out through the use of Large Eddy Simulation and Ffowcs Williams–Hawkings model for noise prediction.

The technique combines a previously developed model for noise from disc sources with a boundary integral equation method for scattering from the duct surface.

The numerical model for noise prediction is developed based on the combination of spatial train track bridge coupled vibration theory and Statistical Energy Analysis SEAA).

It is concluded that the equal energy concept does not meet the requirement for a biologically relevant model for noise exposure.

Other approaches have involved various statistical models for noise and noisy speech [5], and discriminative weight training (DWT) scheme [6].

Accounting for uncertainty in σ Simulations under different distributional models for noise in SUVmax show that it is the reciprocal operation involved in calculating the relative change, rather than the exact form of the distribution, that drives the magnitude of the estimated percentiles.

This allows for further study of the pattern's form (e.g., comparison with deterministic dynamic gene regulation models), as well as the model for the noise (e.g., to detect whether noise is additive or multiplicative).

Models for noises in different phases are established and the corresponding strategies for reducing noises are given.

Noise attenuation is carried out by developing noise models for thermal noise in single section input filters of Buck, Boost and Buck-Boost DC/DC converters.