System Identification of TP Film Evaporation by Using Nearly Equivalent NN Model

This paper presents a technique, called "nearly equivalent neural network (NN) model" in the application of nonlinear system identification. This technique is expected to adequately to catch the behavior of the nonlinear system. To demonstrate the new technique proposed, the evaporation system of TP decoration film was analyzed. The complex relationship between the film's transmittance and its possible influencing factors was identified. For the comparison, the same simulations were also performed by using the conventional neural network with the standard steepest descent error back-propagation (BP) learning algorithm.