Recurrent Polynomial and Neural Structures in Modelling of a Neutralisation Process

This work discusses modelling of a neutralisation process by means of two recurrent modelling techniques: polynomials and neural networks. Model structures and training algorithms are shortly discussed. Two recurrent model classes are compared in terms of accuracy and complexity. Advantages of neural models are emphasised.