Convergence properties of the generalised least squares identitication method
Convergence properties of the generalized least squares method are analyzed. The method can be interpreted as optimization of a likelihood function. The number of local maximum points of the likelihood function is examined. It is shown that this number is influenced by the signal to noise ratio. This theoretical result is illustrated by numerical examples using plant measurements. It is also prove