signal analysis and process modelling

• correlation, ranked correlation, cluster analysis and feature extraction
• time series analysis and noise modelling
• linear process modelling using least square techniques (LS, PCR, PLS, TLS), structure selection methods (forward, backward, stepwise) and validation techniques (cross validation, PRESS, Mallows C(p), adjusted R²)
• adaptive identification and parameter estimation
• nonlinear dynamical modelling using filter chains, nonlinear expansion techniques
• identification of parameter non linear models using optimisation techniques