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A hybrid growing ENFN-based neuro-fuzzy system and its rapid deep learning

An architecture and learning methods for a growing neuro-fuzzy system that enlarges an amount of layers and tunes their synaptic weights in an online way are introduced in the paper. A structure of the hybrid system is built with the help of extended neo-fuzzy neurons which are characterized by improved approximating capabilities. The main peculiar feature of the introduced system is a learning method for each structural element that is carried out sequentially in an online manner.