Figure 1 shows that individual measurement values hover around a mean value and the difference between the mean value and true value is the systematic error of ...

Bayesian uncertainty analysis represents a powerful statistical framework that integrates prior knowledge with observed measurement data to quantify uncertainty in a consistent probabilistic manner.

All measurements are subject to error. When a reportable value is derived from a measurement or series of measurements, this value is only an estimate of the “true ...

Data that are collected for the production of official statistics or, more generally, for statistical analyses nearly always contain measurement errors. National statistical institutes, other ...

Given the potentially strong, adverse effects of measurement error and the possibility of minimizing these using Hidden Markov models (HMMs), the aim of this thesis ...

Very often, in the test and measurement industry, a measurement is made by instrumentation, which is often subject to errors. It is difficult to estimate the true value of the measured quantity given ...

Particle analysis is a crucial step in the quality control of bulk materials and is performed in laboratories worldwide. The methods used have usually been established for years and are rarely ...

The analysis of electrical signals, otherwise known as signal analysis, is a fundamental challenge for virtually all electronic design engineers and scientists. While it provides valuable insight into ...