Input-output modelling with decomposed neuro-fuzzy ARX modelGolob, Marjan (Avtor) Tovornik, Boris (Avtor) input-output modellingfuzzy ARX modelneuro-fuzzy systemThis paper presents a new neuro-fuzzy system based model, which is useful for the modelling of nonlinear dynamic systems. The new proposed model constitutes a soft computing method, namely, reasoning with a fuzzy inference system (FIS) and an optimisation by the neural-network learning algorithm. A structure, named the decomposed neuro-fuzzy ARX model is proposed. This structure is based on decomposition of the FIS. An evolution of a learning algorithm for the decomposed fuzzy model is suggested. A comparative study of dynamic system identification using conventional FIS models and the proposed neuro-fuzzy ARX model is presented for Box-Jenkins data set.20082012-06-01 10:56:11Neznano27387UDK: 007.52:681.5COBISS_ID: 11577622ISSN pri članku: 0925-2312NUK URN: URN:SI:UM:DK:01C9OBKUsl