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Signal averaging is a signal processing technique applied in the time domain, intended to increase the strength of a signal relative to noise that is obscuring it. By averaging a set of replicate measurements, the signal-to-noise ratio (SNR) will be increased, ideally in proportion to the square root of the number of measurements.
Schmidt, in particular, accomplished this by first deriving a complete geometric solution in the absence of noise, then cleverly extending the geometric concepts to obtain a reasonable approximate solution in the presence of noise. The resulting algorithm was called MUSIC (MUltiple SIgnal Classification) and has been widely studied.
If the noise has expected value of zero, as is common, the denominator is its variance, the square of its standard deviation σ N. The signal and the noise must be measured the same way, for example as voltages across the same impedance. Their root mean squares can alternatively be used according to:
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Brightline noisy; here's how to install quiet zones. Having come from Connecticut almost seven years ago, I can tell you that its installation of the wayside/automated quiet-zone horn system made ...
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A use variance is a variance that authorizes a land use not normally permitted by the zoning ordinance. [2] Such a variance has much in common with a special-use permit (sometimes known as a conditional use permit). Some municipalities do not offer this process, opting to handle such situations under special use permits instead.
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