Signal to Noise Ratio PDF
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This document explains the concept of signal-to-noise ratio (SNR) in analytical methods. It describes how SNR is calculated and how noise affects measurements. It also discusses instrumental noise and its sources. The document emphasizes that noise is inherent in analytical measurements and is independent of the signal.
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# Signal to Noise Ratio * The signal-to-noise ratio (S/N) is a much more useful figure of merit than noise alone for describing the quality of an analytical method or the performance of an instrument * Signal to noise ratio (SNR) = Ratio of signal level to noise level * This ratio describes the qua...
# Signal to Noise Ratio * The signal-to-noise ratio (S/N) is a much more useful figure of merit than noise alone for describing the quality of an analytical method or the performance of an instrument * Signal to noise ratio (SNR) = Ratio of signal level to noise level * This ratio describes the quality of instrumental method ## SNR * SNR > 1, The signal is more than the noise. * SNR < 1, the noise level is bigger than the signal level. * The impact of noise increases as the signal is lowest * The signal processors: * Amplifier → increase signal * Attenuator → decrease noise ## Instrumental Noise * Noise is associated with each component of an instrument-that is, with the source, the input transducer, all signal-processing elements, and the output transducer. * Some types of noise are impossible to avoid in a measurement * Noise-free data can never be realized in the lab. ## Signals and Noise * In most measurements, the average strength of the noise N is constant and independent of the magnitude of the signal S. * The effect of noise on the relative error of a measurement becomes greater as the quantity being measured decreases in magnitude. ## Signal to Noise Ratio * There is always some noise in analytical signals * Noise is independent on the signal * **SIGNAL** -> Information about the analyte * **NOISE** -> Unwanted Information not related to analyte