This paper proposes a novel learning algorithm benefitting from square-root cubature Kalman filters for training recurrent interval type-2 fuzzy neural networks. The recurrence property in this network is feeding the output of each input to itself. Simulations results show the effectiveness of the proposed network and the proposed learning algorithm.
