Abstract
A common technique applied during an assay is averaging several repeated measurements in order to obtain a more accurate result. This approach is suitable for most applications. However, in the case of impulsive disturbances which affect the measured object, averaging is not optimal. In the paper, the properties of impulsive disturbances are described and it is explained why averaging is suitable for Gaussian disturbances and unsuitable for impulse ones. The iteratively reweighted least squares method, popular among researchers dealing with signal processing, has been simplified, allowing analysts to use it easily, and it has been adopted to calculate a weighted mean which is more reliable. The properties of the weighted mean have been determined based on Monte Carlo simulations and an analytical signal obtained from an ion-selective electrode. The results shown that the most reliable results are obtained when the average is replaced by such weighted mean, which reduces to the median filtration – then the obtained results are in some cases a bit worse but far less sensitive to impulses.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
