Maximum likelihood identification of a heat diffusion process: a pole clustering effect

Parametric models of a one-dimensional heat diffusion process are determined using the maximum likelihood method. The process is a linear, infinite dimensional system. Statistical teats indicate that the appropriate orders of the models obtained are relatively low. It is found empirically that successive terms in the modal expansion of the transfer function of the process, having gain factors of the same sign, are identified as a single term.