Abstract
It is argued, in this paper, that the core operation underlying any measurement – the inverse modelling under uncertainty – is equivalent to quantitative abductive reasoning which consists in the selection of the best estimate of a measurand (i.e. a quantity to be measured) in a set of admissible solutions, using a priori information: (i) on the measurand, (ii) on the measuring system coupled with an object under measurement, and (iii) on the influence of the environment including the user of the measurement results. There are two key premises of this claim: a systematic interpretation of measurement in terms of inverse problems, proposed earlier by the author, and a logical link between inverse problems and abduction, identified by the Finnish philosopher of science Ilkka Niiniluoto. The title claim of this paper is illustrated with an expanded example of measuring optical spectrum by means of a low-resolution spectrometer.
Generalized least-squares solutions to quasi-linear inverse problems with a priori information.