Fast determination of plasma parameters

Fast Analysis of diagnostic signals of a tokamak discharge is demonstrated by using 4 fundamentally different techniques. A comparison between Function Parametrization (FP), Canonical Correlation Analysis (CCA) and a particular Neural Network (NN) configuration known as the Multi Layer Perceptron (MLP) is carried out, thereby taking a unique linear model based on a Singular Value Decomposition (SVD) as a reference. The various techniques provide all functional representations of characteristic plasma parameters in terms of the values of the measurements and are based on an analysis of a large, experimentally achieved database. A brief mathematical description of the various techniques is given here, followed by two particular applications to TORE SUPRA diagnostic data. The first problem is concerned with the identification of the plasma boundary parameters using the poloidal field and differential poloidal flux measurements. A second application involves the interpretation of line integrated data from the multichannel interfero-polarimeter to obtain the central value of the safety factor. (author) 4 refs., 3 figs