Add to ORKGIn many real-life situations, we are interested in the physical quantities that are difficult or even impossible to measure directly. To estimate the value of such quantity y, we measure the values of auxiliary quantities x1 ; : : : ; xn that are related to y by a known functional relation y = f(x1 ; : : : ; xn ), and we then use the results e x i of measuring x i to find the desired estimate e y = f(ex1 ; : : : ; e xn ). Due to measurement errors, the measured values e x i are slightly different from the actual (unknown) values x i ; as a result, our estimate e y is different from the actual value y = f(x1 ; : : : ; xn) of the desired quantity
Applications of interval computations usually assume that while we only know an interval containing ...
In statistical analysis, we usually use the observed sample values x1, ..., xn to compute the values...
Applications of interval computations usually assume that while we only know an interval containing ...
In many real-life situations, we are interested in the physical quantities that are difficult or eve...
In many real-life situations, we are interested in the value of a physical quantity y that is diffic...
In many practical situations, the quantity of interest is difficult to measure directly. In such sit...
Why indirect measurements? In many real-life situations, we are interested in the value of a physica...
In many practical applications, we are interested in the values of the quantities y1, ..., ym which ...
To predict values of future quantities, we apply algorithms to the current and past measurement resu...
In many practical problems, we need to process measurement results. For example, we need such data p...
Abstract. For a numerical physical quantity v, because of the mea-surement imprecision, the measurem...
In many practical situations, we only know the upper bound D on the (absolute value of the) measurem...
In many practical situations, the only information that we have about measurement errors is the uppe...
A measurement result is incomplete without a statement of its 'uncertainty' or 'margin of error'. Bu...
For a numerical physical quantity v, because of the measurement imprecision, the measurement result ...
Applications of interval computations usually assume that while we only know an interval containing ...
In statistical analysis, we usually use the observed sample values x1, ..., xn to compute the values...
Applications of interval computations usually assume that while we only know an interval containing ...
In many real-life situations, we are interested in the physical quantities that are difficult or eve...
In many real-life situations, we are interested in the value of a physical quantity y that is diffic...
In many practical situations, the quantity of interest is difficult to measure directly. In such sit...
Why indirect measurements? In many real-life situations, we are interested in the value of a physica...
In many practical applications, we are interested in the values of the quantities y1, ..., ym which ...
To predict values of future quantities, we apply algorithms to the current and past measurement resu...
In many practical problems, we need to process measurement results. For example, we need such data p...
Abstract. For a numerical physical quantity v, because of the mea-surement imprecision, the measurem...
In many practical situations, we only know the upper bound D on the (absolute value of the) measurem...
In many practical situations, the only information that we have about measurement errors is the uppe...
A measurement result is incomplete without a statement of its 'uncertainty' or 'margin of error'. Bu...
For a numerical physical quantity v, because of the measurement imprecision, the measurement result ...
Applications of interval computations usually assume that while we only know an interval containing ...
In statistical analysis, we usually use the observed sample values x1, ..., xn to compute the values...
Applications of interval computations usually assume that while we only know an interval containing ...