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Daubechies 2 is the best preference for long range dependent fractional Gaussian noise.
Results show that the equivalent sound pressure level and noise criterion are better criteria than noise rating when correlated with subjective responses.
Proceedings ArticleDOI
Kevin Massey, Richard Gaeta 
07 Jun 2010
20 Citations
The results indicate that propeller noise and engine exhaust noise are generally of equal importance for typical UAVs.
Two novel methods are presented here, which could significantly improve the existing analytical noise models.
These noise reduction filters are demonstrated to deliver a better noise reduction performance especially in low input signal-to-noise-ratio scenarios.
Of these, the DCSK and FM-DCSK techniques offer the best noise performance.
Our results indicate (i) that noise discounts are overestimated in cross-sectional studies because aircraft noise tends to be negatively correlated with omitted neighborhood and housing amenities and (ii) that noise effects are unlikely to be constant over the entire noise range.
They are also robust to noise.
Combustion noise analysis provided the best correlation to microphone noise, especially at lower speeds where engine noise is dominated by combustion noise rather than mechanical noise.
They are especially preferred if the underlying noise deviates from Gaussian with the impulsive noise components.
Aircraft noise impact around airports will increase corresponding to the predicted growth in air-traffic if no measures for aircraft source noise reduction are taken or noise abatement flight procedures are developed.
Finally, experiments in a reverberant room reveal that the polyhedral microphone array associated with both criteria provides the best noise source map.
To the authors' knowledge, these results demonstrate the best silicon low-noise amplifier performance up to date in this frequency range.
To the authors' knowledge, this demonstrates the best noise performance up to date on a silicon platform in this frequency range.
With this tool we are able to quantify different noise sources, which is important to determine realistic noise specifications for the design of electronic neural recording interfaces.
Numerical results are presented which suggest that different noise sources can impact performance in profoundly different ways.
Both extensions are able to preserve binaural cues for the speech and noise sources, while still achieving significant noise reduction performance.