Signal-to-noise ratio (SNR, S/NR or S/N) is idea with roots in cybernetics and information theory. It is extensively used in electronic engineering, but has found applications in other fields, such as encoding errors in genetic material. SNR has even entered popular culture, when the particularly incoherent speech of a politician or generic celebrity is described as having an extremely low signal to noise ratio.
SNR is high when the totality of received information is mostly of interest, but is low when much of the received signal is extraneous.
In this context, noise is any signal, in a channel between sender and receiver, that is not part of the useful content that the receiver desires to hear from the sender.
There are several ways to improve the generic SNR:
In spectroscopic methods, the S/N ratio can be increased by multiple acquisitions of data because while noise is random, the signal of interest is not. Thus, if a signal is recorded and summed times, the signal intensity increases -fold, while the noise increases by , leading to a S/N improvement of . A much larger increase can be obtained by cooling the electronic components to near liquid helium temperatures, which greatly decreases electronic noise.
Do note that a living receiver may be able to improve the effective SNR by the brain's ability to recognize patterns and suppress noise. In telephony, for example, the mean opinion score is a technique of surveying the quality of voice messages as perceived by human listeners with normal hearing.
An online calculator page, with derivations, discusses Johnson noise, Nyquist noise, and white noise. [1]
There are specialized techniques for improving SNR in imaging.[2]