A deep cascade neuro-fuzzy system for high-dimensional online fuzzy clustering

A deep cascade system (based on neuro-fuzzy nodes) and its online learning procedure are proposed in this paper. A number of layers can grow unlimitedly during a self-learning procedure. The system is based on nodes of a special type. A goal function of a special type is used for probabilistic high-dimensional fuzzy clustering. To assess a clustering quality of data processing, a neuron's architecture of a special type is introduced.