Function parametrization: Difference between revisions
no edit summary
No edit summary |
No edit summary |
||
Line 1: | Line 1: | ||
Function Parametrization (FP) is a technique to provide fast (real-time) construction of system parameters from a set of diverse measurements. | Function Parametrization (FP) is a technique to provide fast (real-time) construction of system parameters from a set of diverse measurements. It consists of the numerical determination, by statistical regression on a database of simulated states, of simple functional representations | ||
<ref>B.J. Braams, W. Jilge, and K. Lackner, ''Fast determination of plasma parameters through function parametrization'', Nucl. Fusion '''26''' (1986) 699</ref> | of parameters characterizing the state of a particular physical system, where the arguments of the functions are statistically independent combinations of diagnostic raw measurements of the system. | ||
The technique, developed by H. Wind for the purpose of momentum determination from spark chamber data <ref> Wind, H., `Function Parametrization' | |||
in ``Proceedings of the 1972 CERN Computing and Data Processing School'', CERN 72--21, 1972, pp.~53--106.} </ref> , <ref>Wind, H., | |||
(a)`Principal component analysis and its application to track finding', (b) `interpolation and function representation' | |||
in ``Formulae and Methods in Experimental Data Evaluation'',Vol. 3, European Physical Society, Geneva, 1984</ref>, was introduced by B. Braams to plasma physics, | |||
where its first application (to the analysis of equilibrium magnetic measurements on the circular cross-section ASDEX tokamak) together with a succinct mathematical description, appeared in | |||
<ref>B.J. Braams, W. Jilge, and K. Lackner, ''Fast determination of plasma parameters through function parametrization'', Nucl. Fusion '''26''' (1986) 699</ref>. | |||
== Method == | == Method == | ||
The application of the technique requires that a model exists to compute the response of the measurements (''q'') to variations of the system parameters (''p''), i.e. the mapping ''q = M(p)'' is known. | The application of the technique requires that a model exists to compute the response of the measurements (''q'') to variations of the system parameters (''p''), i.e. the mapping ''q = M(p)'' is known. |