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Signal-to-noise ratio (SNR or S/N) is a measure used in science and engineering that compares the level of a desired signal to the level of background noise. SNR is defined as the ratio of signal power to noise power , often expressed in decibels .
Peak signal-to-noise ratio (PSNR) is an engineering term for the ratio between the maximum possible power of a signal and the power of corrupting noise that affects the fidelity of its representation.
Traditionally, SNR is defined to be the ratio of the average signal value to the standard deviation of the signal : [2] [3] = when the signal is an optical intensity, or as the square of this value if the signal and noise are viewed as amplitudes (field quantities).
The ratio of (a) total received power, i.e., the signal to (b) the noise-plus-distortion power. This is modeled by the equation above. [2] The ratio of (a) the power of a test signal, i.e. a sine wave, to (b) the residual received power, i.e. noise-plus-distortion power. With this definition, it is possible to have a SINAD level less than one.
This is an example of a case where sensivity is defined as the minimum input signal required to produce a specified output signal having a specified signal-to-noise ratio. [2] This definition has the advantage that the sensitivity is closely related to the detection limit of a sensor if the minimum detectable SNR o is specified .
The carrier-to-noise ratio is defined as the ratio of the received modulated carrier signal power C to the received noise power N after the receiver filters: =. When both carrier and noise are measured across the same impedance, this ratio can equivalently be given as:
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Noise reduction, the recovery of the original signal from the noise-corrupted one, is a very common goal in the design of signal processing systems, especially filters. The mathematical limits for noise removal are set by information theory .