Deep Evolving Stacking Convex Cascade Neo-Fuzzy Network and Its Rapid Learning
Yevgeniy V. Bodyanskiy, Galina Setlak, Olena А. Vynokurova, Iryna Pliss, Олена Бойко · Annals of Computer Science and Information Systems · 2018
A deep evolving stacking convex neo-fuzzy network is proposed.It is a feedforward cascade hybrid system, the layers-stacks of which are formed by generalized neo-fuzzy neurons that implement Wang-Mendel fuzzy reasoning.The optimal in the sense of speed algorithms are proposed for its learning.Due to independent layer adjustment, parallelization of calculations in non-linear synapses and optimization of learning processes, the proposed network has high speed that allows to process information in online mode.