Background noise exists ubiquitously in analytical instruments, whether or not a sample is applied to the instrument. This document is concerned with mathematical methodologies for estimating the minimum detectable value in case that the most predominant source of measurement uncertainty is background noise. The minimum detectable value can directly and mathematically be derived from the stochastic characteristics of the background noise.<\/p>\n
This document specifies basic methods to<\/p>\n
extract the stochastic properties of the background noise,<\/p>\n<\/li>\n
use the stochastic properties to estimate the standard deviation (SD) or coefficient of variation (CV) of the response variable, and<\/p>\n<\/li>\n
calculate the minimum detectable value based on the SD or CV obtained above.<\/p>\n<\/li>\n<\/ul>\n
The methods described in this document are useful for checking the detection of a certain substance by various types of measurement equipment in which the background noise of the instrumental output predominates over the other sources of measurement uncertainty. Feasible choices are visible and ultraviolet absorption spectrometry, atomic absorption spectrometry, atomic fluorescence spectrometry, luminescence spectrometry, liquid chromatography and gas chromatography.<\/p>\n
| PDF Pages<\/th>\n | PDF Title<\/th>\n<\/tr>\n | ||||||
|---|---|---|---|---|---|---|---|
| 2<\/td>\n | National foreword <\/td>\n<\/tr>\n | ||||||
| 6<\/td>\n | Foreword <\/td>\n<\/tr>\n | ||||||
| 7<\/td>\n | Introduction <\/td>\n<\/tr>\n | ||||||
| 9<\/td>\n | 1 Scope 2 Normative references <\/td>\n<\/tr>\n | ||||||
| 10<\/td>\n | 3 Terms and definitions <\/td>\n<\/tr>\n | ||||||
| 11<\/td>\n | 4 Quantitative analysis and background noise 4.1 Error sources of analysis 4.2 Random processes in background <\/td>\n<\/tr>\n | ||||||
| 12<\/td>\n | 5 Theories for precision 5.1 Theory based on auto-covariance function <\/td>\n<\/tr>\n | ||||||
| 13<\/td>\n | 5.2 Theory based on power spectrum <\/td>\n<\/tr>\n | ||||||
| 17<\/td>\n | 6 Practical use of FUMI theory 6.1 Estimation of noise parameters by Fourier transform <\/td>\n<\/tr>\n | ||||||
| 18<\/td>\n | 6.2 Estimation of noise parameters by autocovariance function <\/td>\n<\/tr>\n | ||||||
| 19<\/td>\n | 6.3 Procedures for estimation of SD <\/td>\n<\/tr>\n | ||||||
| 22<\/td>\n | Annex A (informative) Symbols and abbreviated terms used in this document <\/td>\n<\/tr>\n | ||||||
| 23<\/td>\n | Annex B (informative) Derivation of Formula (7) <\/td>\n<\/tr>\n | ||||||
| 24<\/td>\n | Annex C (informative) Derivation of Formulae (14) to (16) <\/td>\n<\/tr>\n | ||||||
| 26<\/td>\n | Bibliography <\/td>\n<\/tr>\n<\/table>\n","protected":false},"excerpt":{"rendered":" Capability of detection – Methodology based on stochastic properties of instrumental noise<\/b><\/p>\n |